A reader points out that David Shenk is blogging genetics & IQ over at The Atlantic. If you have some free time to kill in comment sections, you might be interested. To get a flavor, a post titled The Truth About IQ has a footnote to Stephen Jay Gould's Mismeasure of Man.

Labels: IQ

IQ Explains Some Of The Difference In Heart Disease Between People Of High And Low Socio-economic Status:

Authors of the study published in the European Heart Journal on 15 July...analysed data from a group of 4,289 former soldiers in the USA. They found that IQ explained more than 20% of the difference in mortality between people from socio-economically disadvantaged backgrounds compared to those from more advantaged backgrounds. Importantly, this was in addition to the classical, known risk factors for heart disease, such as smoking and obesity.
...
"The difference between the second and third analyses showed that IQ alone explained a further 23% of the differences in mortality between the higher and lower ends of the socio-economic spectrum, in addition to the other, known risk factors," said Dr Batty. “IQ wasn’t a magic bullet in this study, but this psychological variable had additional explanatory power on top of the classic variables such as smoking, high blood pressure, high blood glucose and obesity. It has partially explained the differences in death from heart disease and all causes."
...
...there could be three possible explanations for Dr Batty's findings: "(i) intelligence might lead to greater knowledge about how to pursue healthy behaviours; (ii) intelligence may "cause" socioeconomic position, i.e. more intelligence leads to more education, income, occupational prestige . . .; and (iii) intelligence may be a marker for something else, and it is that something else, early life exposures, for example, that leads to mortality."....

When correlations between socioeconomic status and health outcomes emerge, generally there is an assumption that the differences are due to disparate access to health care, or, more vaguely to the mysterious effect of low social status on someone's health. Matt Ridley actually posited the second explanation in Genome. As noted above intelligence does not explain everything, but its role is unfortunately not considered all too often. If, for example, intelligence has some correlation with time preference, and time preference modulates one's risk calculus, the causal chain which might result in disparate health outcomes is obvious. In The Myth of the Rational Voter Bryan Caplan has a reasonable number of references to the literature which show that the more intelligent may not be particularly rational in any absolute sense, but they are far more rational than the conventionally dull in a relative sense.

Labels: human biodiversity, IQ

A study from Wicherts et al published online in the journal Intelligence today:

On the basis of several reviews of the literature, Lynn... concluded that the average IQ of the Black population of sub-Saharan Africa lies below 70. In this paper, the authors systematically review published empirical data on the performance of Africans on the following IQ tests: Draw-A-Man (DAM) test, Kaufman-Assessment Battery for Children (K-ABC), the Wechsler scales (WAIS & WISC), and several other IQ tests (but not the Raven's tests)... Results show that average IQ of Africans on these tests is approximately 82 when compared to UK norms.

UPDATE: Tables and Figures below the fold



Table 4. Results by subsets of samples.



Table 5. Estimates of mean IQs per country on the basis of studies in Table 2 and studies from the Raven's study.



Fig. 1. Scatterplot of data from study by Lynn (2006) and Lynn and Vanhanen (2006).



Fig. 2. Scatterplot of data from study by Rindermann (2007).



Fig. 3. Scatterplot of data from study by Lynn and Mikk (2007).



Fig. 4. Scatterplot of data from study by Lynn et al. (2007).



Fig. 5. Mean of samples that meet our inclusion criteria against the inverse of the standard error.



Fig. 6. Mean of samples from studies published prior to 2006 against the inverse of the standard error.

Labels: IQ

A simple but powerful way to determine whether or not there's a irrational bubble is to look for a lot of people who are participating in a trend who have no business doing so. For instance, a Mexican strawberry-picker making $15,000 a year who gets a $720,000 loan for a home. If these don't-belong-there people make up a larger and larger fraction of all who get loans, that strongly suggests that everyone is trying to get in on a speculative bubble -- and that the gatekeepers of the activity are increasingly debauching their entry standards to accommodate the losers.

One datum that suggests an irrational bubble in education is that a much larger fraction of the population is going to college now, and that not surprisingly the average IQ of college students has declined by about 2/3 s.d. -- admissions boards began to scrape deeper down into the sludgebucket of society.

How about looking even earlier? High school is compulsory, so we can't really use high school enrollment to judge whether there's a bubble or not. But what about the sub-group of high school that ostensibly is there to prepare college-bound students for college? That is up to the choice of students, perhaps being bullied by their parents. There is strong evidence even at this early stage of an irrational bubble.

What got me thinking about this was a recent NYT article on how teachers feel about the Advanced Placement program, which is based on a report from the Thomas B. Fordham Institute. The key item that popped out was the claim that participation in the AP program has exploded in recent years, and that this has made a fair fraction of teachers anxious about whether there are students there who shouldn't be. This sure smells like a bubble.

First, let's make sure that the AP program really is exploding as they say, and then we'll see if there's a rational basis for it or not. To measure participation in the AP program, I simply took the number of AP tests taken and divided it by the high school population size. (The AP data are here, and the high school pop data are here, Table A-1.) The AP data go back to 1988, while the high school pop data end in 2007, so I looked at the period from 1988 to 2007. Here are both the total number of AP tests taken and the per capita rate:


An exponential trend accounts for 99.8% of the year-to-year variation for the total number of tests taken, and 99.2% in the per capita case. So, clearly participation in the AP program has been exploding at least since 1988.

Now, is there a sound basis for this increase -- like, maybe kids these days are just getting exponentially smarter? Without looking at the data, we know this is wrong since the main determinant of doing well in AP classes is IQ, and that is influenced mostly by genes and unpredictable aspects of the environment, which haven't been changing so rapidly from one year to the next.

Turning to data on how well 17 year-olds are doing academically, let's look at some tables from the 2007 version of the Digest of Education Statistics (all under Chapter 2, and then Educational Achievement). Table 112 shows that on the National Assessment of Educational Progress, the average reading score for 17 y.o.s did not change from 1971 to 2004. Table 115 shows that the percent of 17 y.o. students who are at the 300 level or above in reading did not change from 1971 to 2004. Tables 125 and 126 show the same lack of change for math skills tested by the NAEP. Table 135 shows that the average Critical Reading score on the SAT did not change from 1988 onward -- indeed, it was steady back to about 1976, and had been declining before then. There was a modest uptick in Math scores (15 points, or 0.15 s.d.). The Critical Reading or Verbal score is more highly g-loaded than the Math score for the SAT, or is a better measure of IQ, which means the apparent uptick in Math scores may not mean as much as we'd think.

Taken together, these data show that the academic fundamentals of high schoolers has not changed since the 1970s. If there has been no upswing at all in the fundamentals -- let alone an exponential one -- then the explosion of the AP program is accounted for completely by irrational factors. It seems just like the housing bubble -- the size of deserving borrowers didn't explode, so the surge in borrowing must have been due to a bunch of undeserving people pouring into the building, namely low-income people. Here are two graphs showing that this happened in the AP program too:




The first shows the distribution of AP scores, where 5 is greatest. You can check the numbers for yourself in the previous link to the AP data, but there has been no change in the percent of all tests that received a score of 4 or 5 -- there have not been more and more smarties piling into AP classrooms, at least not since 1988. Therefore, everyone who deserved to be there was already there. However, the percent of all tests receiving a score of 1 -- telling the student, "why did you even bother?" -- has doubled from 10% to 21%. Those receiving a 2 shrunk a tiny amount, from about 23% to 21%. But those receiving a 3 declined from about 32% to 24%. This means that, unlike for smarties, more and more dummies have been allowed into the AP program.

This is reflected in the change in the mean and standard deviation of test scores: keeping the smarties fixed while adding a lot more dummies will drag down the mean and increase the heterogeneity or variance. That's analogous to the housing bubble causing a decline in the mean creditworthiness of the population of borrowers, and an increase in their heterogeneity, as both the sound and the unsound begin to rub shoulders in loan offices. And just as lenders increasingly cheapened their standards by not requiring down payments or proof of income, so high school teachers and administrators have allowed increasingly ill-prepared -- stupid -- students into the AP program.

In sum, there is very strong evidence from AP tests for a speculative bubble in education. Most of what I've read on whether or not such a bubble exists has focused on college -- soaring tuition, more and therefore dumber students, and so on. These data, though, show that the mania extends even to high school, not just higher ed. For at least the past five years, there have been many news stories about competitive admission to pre-school, so perhaps someone could dig up some numbers to show an exponential increase there too that can't be rationalized by a change in fundamentals. In any case, it's clear that this bubble is much more general than the college data suggest.

Curiously, the phrase "education bubble" has not appeared at all in the NYT, although it has appeared many times in the blogs that the newspaper hosts. Googling the phrase gets 39,000 hits. Rises and falls in tuition get plenty of coverage, but that doesn't show that the reporters are aware of the irrational bubble -- they just think it's unfair, that college should be cheaper so that more can attend. But just as no one was allowed to say that most low-income borrowers were undeserving of home loans since they were disproportionately black and Hispanic, so we aren't allowed to say that a lot of college students are nowhere near being "college material" -- that would violate the "demotic life and times," as Jacques Barzun has dubbed the zeitgeist from roughly the 1960s until today. We cripple our minds by imbibing political correctness.

The bursting of the education bubble may be decades away -- it sure has been going on for awhile, so its period may be much longer than that of the housing or stock market bubbles. Let's just hope that when it happens, it will turn out that hedge funds and investment banks won't have exposed themselves to all of this silliness, and that we won't be plunged into another multi-year recession.

Labels: Economics, education, IQ, Sociology

As many have noted, The New Republic is now publishing perceptions that Sonia Sotomayor is not that intelligent. Granted, even if affirmative action played a role in her acceptance to Princeton and Yale law school, the fact that she graduated and passed the bar suggests a minimum threshold of ability. But that's not good enough, it seems that many liberals would like someone who can go toe-to-toe with the conservatives on the court intellectually, and she doesn't pass the grade on that elevated level. When the stakes are high, and a Supreme Court position is arguably one of the most powerful positions within the American government, the perceived marginal returns on more g become stark for those who would pooh-pooh it in other contexts.

Addendum: As noted in the comments, yes, it doesn't take a genius to know how political confederates want you to rule. I happen to think that most moral & political reasoning is really moral & political rationalization. So the key is simply to find people who can argue in a crisp manner in favor of positions they already hold a priori. More generally I accept there is some systematic tendencies in terms of what the smart, as opposed to the dumb, believe, regardless of their ideology. See The Myth of the Rational Voter for examples. But let's not confuse the signal for the noise.

Labels: IQ, politics

Steve points me to a profile of Greg & Henry, with a focus on Jewish genetics & smarts.

Labels: IQ, Jews

Several people have emailed me (and emails and forward are appreciated by the way) about two articles in The New York Times about IQ. IQ Harmed by Epilepsy Drug in Utero, which Steve's already commented on. And the most emailed article currently, Nicholas Kristof's How to Raise Our IQ. Some of you who have been reading this blog since the beginning might have noticed that I long ago stopped talking much about psychometrics. Why? I'd rather not waste my time trying to convince smart people that they are actually smarter than stupid people. If I had a penny every time someone with an elite college education in the hard sciences explained that "they don't believe in IQ".... Of course, on the other hand these aren't the huge majority of people. Many who were nerds or of high intelligence know that there's a qualitative difference between themselves and the herd, in particular those from families with several siblings where psychometric variance is rather obvious. How much more "shared" can environment exactly get?

But in any case, many of the intelligent refuse to assent to the position that intelligence actually exists, and that it can be measured. A few conversations aren't going change opinions here, as the opinions aren't based on empirical data. Rather, it's a theory to which one is socialized (and which socialization can reverse, but this requires a great deal of time investment which isn't going to happen with most people). My own experience with the crowd that runs with Robin Hanson and Eliezer Yudkowsky is that 1) they tend toward the retarded end of social intelligence 2) are invariably accepting of, or open to, the reality of g. In other words, my assumption is that most people who "don't believe in intelligence," don't for reasons of socialization, because they know the rewards built into the incentive structure of human groups for conformity. Of course, there is "believe," and then there is believe. The same people who don't believe in intelligence are proud of their GRE scores, convinced that Republicans and religious people have lower IQs, and outraged when the mentally deficient, as measured on IQ tests, are executed. This probably reflects some mental modularity. People might say they don't believe in IQ, but the decisions they make are to some extent informed by the assumption that intelligence exists, and individuals vary. This shouldn't be a surprise, our executive functions have only a loose control over the different subfunctions which define our cognition. Ironically it might reflect the limits of the conscious rationalin enforcing its well on subconsciously operating modules. The long arm of intelligence reaches only so far into the crevasses of one's mind.

So the best way to increase the intelligence of your offspring? Fuse your gametes with someone intelligent! You don't even have to believe in intelligence to do this, as many who do just this don't. The main issue isn't that people won't be a position to fuse their gametes with individuals in the same range as themselves in terms of intelligence. Rather, it's that they won't let the fusion come to fruition!

Labels: IQ, psychometrics

Follow up to the post below, Jake Young at Pure Pedantry has a thorough review.

Labels: IQ, Neuroscience

Positive association between cognitive ability and cortical thickness in a representative US sample of healthy 6 to 18 year-olds:

Neuroimaging studies, using various modalities, have evidenced a link between the general intelligence factor (g) and regional brain function and structure in several multimodal association areas. While in the last few years, developments in computational neuroanatomy have made possible the in vivo quantification of cortical thickness, the relationship between cortical thickness and psychometric intelligence has been little studied. Recently, cortical thickness estimations have been improved by the use of an iterative hemisphere-specific template registration algorithm which provides a better between-subject alignment of brain surfaces. Using this improvement, we aimed to further characterize brain regions where cortical thickness was associated with cognitive ability differences and to test the hypothesis that these regions are mostly located in multimodal association areas. We report associations between a general cognitive ability factor (as an estimate of g) derived from the four subtests of the Wechsler Abbreviated Scale of Intelligence and cortical thickness adjusted for age, gender, and scanner in a large sample of healthy children and adolescents (ages 6–18, n = 216) representative of the US population. Significant positive associations were evidenced between the cognitive ability factor and cortical thickness in most multimodal association areas. Results are consistent with a distributed model of intelligence.

See ScienceDaily.

Labels: IQ

Readers of this weblog from back in 2002 know that we used to point to Paul Thompson's research. So see this, Genetics of Brain Fiber Architecture and Intellectual Performance:

The study is the first to analyze genetic and environmental factors that affect brain fiber architecture and its genetic linkage with cognitive function. We assessed white matter integrity voxelwise using diffusion tensor imaging at high magnetic field (4 Tesla), in 92 identical and fraternal twins. White matter integrity, quantified using fractional anisotropy (FA), was used to fit structural equation models (SEM) at each point in the brain, generating three-dimensional maps of heritability. We visualized the anatomical profile of correlations between white matter integrity and full-scale, verbal, and performance intelligence quotients (FIQ, VIQ, and PIQ). White matter integrity (FA) was under strong genetic control and was highly heritable in bilateral frontal....bilateral parietal...and left occipital...lobes, and was correlated with FIQ and PIQ in the cingulum, optic radiations, superior fronto-occipital fasciculus, internal capsule, callosal isthmus, and the corona radiata...for PIQ, corrected for multiple comparisons). In a cross-trait mapping approach, common genetic factors mediated the correlation between IQ and white matter integrity, suggesting a common physiological mechanism for both, and common genetic determination. These genetic brain maps reveal heritable aspects of white matter integrity and should expedite the discovery of single-nucleotide polymorphisms affecting fiber connectivity and cognition.

Here's the summary at ScienceDaily.

Labels: IQ, Neuroscience

In the latest issue of Nature, competing editorials were written on the proposition that scientists should study race and IQ. Steven Ceci and Wendy Williams argued 'Yes', and Steven Rose argued 'No'. In this article I will detail the scientific errors which underly Rose's argument. The scientific reasons offered by him are largely a veneer meant to justify his "radical science" political views, but I will refrain from commenting on his politics until my next post on this.

Rose argues:

the categories of intelligence, race and gender are not definable within the framework required for natural scientific research, failing my first criterion of being well-founded. They also fail the second criterion of being answerable: we lack the theoretical or technical tools to study them.

Let's begin with his critiques of IQ:

to try to capture the many forms of socially expressed intelligent behaviour in a single coefficient — and to rank an entire population in a linear mode, like soldiers on parade lined up by height — excludes most richly intelligent human activities. Social intelligence, emotional intelligence, the intelligent hands of the craftsman or the intelligent intuition of the scientist all elude the 'g' straightjacket

Modern psychometrics isn't claiming that all of a person's intelligence is measured by IQ or g. IQ is used because of its strong and reliable correlations with educational and economic performance, independent of class and race.

Group comparisons of IQ are even more problematic. Attempts have been made to make 'culture-fair' or 'culture-free' tests, as if such a thing were possible, to allow comparisons of 'g' between people from very different societies.

Rose doesn't understand what is meant by "culture fair." It doesn't mean that the test prevents someone's culture from having an effect on their IQ score. Rather, it means that culture does not effect the test's predictive validity. And that is indeed the case. Worldwide the correlations between IQ and economic/educational success are high.

Rose goes on to critique the concept of biological race:

As for 'race', the problem is whether it is a biologically, as opposed to socially, meaningful category. Among geneticists interested in differences in gene frequencies between populations, there is increasing consensus that the word obscures more than it reveals, and should be replaced by the concept of biogeographic ancestry, which makes possible the study of subpopulations for relevant genetic and phenotypic characteristics... Broad divisions between 'white' or 'Caucasian' and 'black' or 'Asian', the groups generally discussed in the context of the IQ debate, especially in the United States, hide genetically important subpopulation differences within these groups.

To begin with, it is biologically meaningful to talk of the 'white race' or the 'asian race.' These categories encapsulate a great deal of genetic variation, and are not arbitrary; as Steve Sailer has pointed out, Cavalli-Sforza's principal components map corresponds to social categories of race.

Furthermore, discussing higher level categories does nothing to obscure lower level categories. If I know someone is a Christian, this doesn't mean I cease to be interested in their denomination. And in fact, psychometricians do study more specific categories than the big 3 races; see for example Jason Malloy's summary of Lynn's worldwide psychometric work.

As for terminology, it is actually irrelevant whether we refer to population groups by their "race" or their "biogeographic ancestry." The former has more social and historical baggage, and the latter is more long-winded, but they both point to the same empirical fact-- group-based genetic differences.

Lastly, the IQ differences between blacks, whites, and asians interest researchers so much simply because the differences in educational/economic outcomes between these groups interest researchers (and the public) more than other group-based differences.

Rose moves on to gender:

the crucial question is whether it is possible to identify a biological — presumably genetic or neurodevelopmental — cause to any difference in the way men and women think and act. The problem is that from the moment of birth, boys and girls are treated differently, which shapes both their growing bodies and brains and how they are expected to behave... Thus, although there are minor average structural and biochemical variations between Western men's and women's brains (such as the volume of some nuclei and the distribution of hormone receptors), speculations on their implications for how men and women may think or behave lack any empirical basis.

There are plenty of research methods that can be used to sidestep the problems that Rose raises here. To name a few, we can look at: kids raised as the opposite gender because of botched genital operations, how hormones correlate with various behaviors, the differences between girl or boy babies in their first months of life, human universals, etc.

Rose closes up the "scientific" portion of his article by citing many of the difficulties which prevent the resolution of the race and IQ debate:

The standard approach of population biologists to estimating the potential genetic contribution to a trait is to make a heritability estimate. Whatever the strengths and weaknesses of this measure within a population, it is essentially just that: a within-population measure, only valid for a given environment. The nature of the equations means that if the environment changes, the heritability estimate changes too...Even if reliable correlations were found between some intelligence test score and a measure of brain physiology or activity held by a specific group, such a correlation says nothing about the direction of causation.

This is an argument for more research, not less. This is an argument for genome-wide association studies, which will allow us to pinpoint the genes that effect intelligence and how they interact with the enviornment. This is an argument for more research on the neuroscience behind IQ and intelligence. This is an argument for further funding of projects to map out the genetic differences between human populations world-wide. This is not an argument for cutting off an important (albeit, politically inconvenient) avenue of science.

Labels: IQ, race

Low-carbohydrate weight-loss diets. Effects on cognition and mood:

To examine how a low-carbohydrate diet affects cognitive performance, women participated in one of two weight-loss diet regimens. Participants self-selected a low-carbohydrate (n = 9) or a reduced-calorie balanced diet similar to that recommended by the American Dietetic Association (ADA diet) (n = 10). Seventy-two hours before beginning their diets and then 48 h, 1, 2, and 3 weeks after starting, participants completed a battery of cognitive tasks assessing visuospatial memory, vigilance attention, memory span, a food-related paired-associates a food Stroop, and the Profile of Moods Scale (POMS) to assess subjective mood. Results showed that during complete withdrawal of dietary carbohydrate, low-carbohydrate dieters performed worse on memory-based tasks than ADA dieters. These impairments were ameliorated after reintroduction of carbohydrates. Low-carbohydrate dieters reported less confusion (POMS) and responded faster during an attention vigilance task (CPT) than ADA dieters. Hunger ratings did not differ between the two diet conditions. The present data show memory impairments during low-carbohydrate diets at a point when available glycogen stores would be at their lowest. A commonly held explanation based on preoccupation with food would not account for these findings. The results also suggest better vigilance attention and reduced self-reported confusion while on the low-carbohydrate diet, although not tied to a specific time point during the diet. Taken together the results suggest that weight-loss diet regimens differentially impact cognitive behavior.

Also at ScienceDaily. Small N's. What were the N's on the Creatine studies???

Labels: IQ

The Audacious Epigone has two interesting posts up right now. Conservative men more intelligent than conservative women; Liberal women more intelligent than liberal men and Politics and IQ; Conservative Democrats and liberal Republicans least intelligent. The titles are self-evident, but, I would add that with hindsight it might make sense that liberal Republicans aren't too bright. If you're a liberal Republican you are probably just in denial, or, confused and dull. When I think liberal Republican I think Tom Campbell or Chris Shays, but these may simply be elite examples who don't reflect the fact that most ideological outliers in parties are just individuals who don't think deeply. For example, someone who was born into a "Republican family," and doesn't reflect much about ideology and so continues to vote Republican despite being liberal. I don't feel I need to explain conservative Democrats, as it seems to me that political exemplars of this class are generally duller than liberal or moderate Democrats.

Note: I know this is kind of a political post, but I'm going to be strict about not letting the comment thread degenerate immediately. So don't get offended if I don't let you through the mod-queue even if I normally do.

Labels: IQ

...is the title of an interesting essay by Ian Deary in this week's Nature. The article is short and quite accessible, and well worth a read.

Labels: IQ

That's the result from a new experimental study of 1,000 people attending truck driving school. The authors tested all of them with Raven's Progressive Matrices, a real IQ test. They then put pairs of them through a prisoner's dilemma game, and found:

[M]easures of cognitive skill [CS] predict social awareness and choices in a sequential Prisoner's Dilemma game. Subjects with higher CS's more accurately forecast others' behavior....[S]ubjects with higher CS's also cooperate more as first movers.

This set of genuine experiments improves on this older paper, which found that students at high-SAT schools cooperated more in prisoner's dilemmas than students at low-SAT schools. Now we know it's not just because posh, high-SAT schools facilitate a "culture of cooperation" or something like that. Smart individuals just figure it out on their own.....

Bottom line: More evidence that smarter groups are more likely to think win-win.

Labels: IQ

It's up, How Jews Became Smart: Anti-"Natural History of Ashkenazi Intelligence" (big PDF). The long-awaited rebuttal to the Natural History of Ashkenazi Intelligence.

Labels: culture, IQ

Recently Charles Murray has promoted the idea that too many people are seeking 4 year degrees: "Let's stop this business of the B.A., this meaningless credential". Last year he wrote in the Wall Street Journal:

If you want to do well [in college], you should have an IQ of 115 or higher. Put another way, it makes sense for only about 15% of the population, 25% if one stretches it, to get a college education. And yet more than ... 40% of all persons in their late teens are trying to go to a four-year college--enough people to absorb everyone down through an IQ of 104.

Several months ago, the Inductivist found this to be a canny estimate: in the 1960s the average college graduate had an IQ very close to 115, and today the average college graduate has an IQ of 105.

But what does this mean for the individual? Murray suggests that college debt, lack of relevant job training, and years of lost workforce wages and experience await those below the 85th percentile:

They are in college to improve their chances of making a good living ... and would do better in vocational training ... two-year colleges ... [are] about right for learning many technical specialties, while four years is unnecessarily long ... Finding a good lawyer or physician is easy. Finding a good carpenter, painter, electrician, plumber, glazier, mason--the list goes on and on--is difficult, and it is a seller's market. Journeymen craftsmen routinely make incomes in the top half of the income distribution while master craftsmen can make six figures.

I find the thinking here plausible, and these seem like testable enough ideas. Luckily, all the relevant variables are included in the General Social Survey.

It's graph day on gnxp. The x axis in the figure below represents the number of correct answers on the 10 question WORDSUM mini IQ test included in the GSS. The y axis represents the respondent's income in constant dollars. The colored lines represent five educational categories, and one occupational category. Moving left to right we see the average income of people in each category as their IQ score increases from 0-10 correct answers. 'Junior college' represents the two-year vocational degree Murray references. And 'Craft and Trade Workers' covers over 50 skilled trade categories like electrician, mason, plumber, carpenter, and mechanic, coded by the survey.


The first observation here is that educational degrees, whether they confer skills or credentials, are more important to income than IQ when minimum thresholds are met. Trade workers, and 2 and 4-year college graduates are not significantly represented in the lowest three IQ categories. Graduate holders have an even higher minimum IQ. Second, income rises within 5 of the 6 categories as IQ increases. Higher IQ generates the biggest pay-off differences between those with advanced degrees, which is consistent with IQ increasing in importance as jobs become more complex. Third, merely earning a Bachelor's degree is a golden ticket. People with average and below average IQs are getting just as much of a financial return out of their 4-year degree as those above the 85th percentile. This suggests many more people of marginal ability should be seeking a Bachelor's degree, not less. Fourth, the two lines for junior college and trade occupations overlap substantially, as we would expect if most people in trade occupations went to trade school. Fifth, and most directly related to Murray's argument, people with 4-year degrees earn much more than people with 2-year degrees and trade jobs at every level of IQ. Average IQ people will get a much, much larger monetary reward from completing a 4 year school than a 2 year school. So the BA is far from being a "meaningless credential" when it comes to "chances of making a good living".

It's possible people with average IQs who complete college are exceptional in other ways. But there is no other empirical evidence that vocational school is better at generating income for those <85th percentile.

Also, secular trends could distort data in the first graph, which combines all survey data from 1972-2006. So the second graph below represents only people who were 35 and older and surveyed between 2000-2006. Fortunately, the results are not too different from the first graph. The IQ categories are condensed and transformed, and we see that 96 is about the minimum to complete 2 and 4 year college, and 111 the minimum for graduate degrees. Again we find that IQ shows no relationship to income for those with a BA, and, in fact, those with lower IQs might profit the most. For those without advanced degrees, people who are moderately above and moderately below average intelligence might earn the most (this balance might be because other socially valued personality traits, like masculinity, are inversely associated with IQ).



So, while I have yet to read Real Education -- which may address these issues -- it would appear that Murray is mistaken in some of his crucial premises.

Still undetermined is if people with 4 year degrees earn a lot more money because they actually acquire important skills, or if inefficient laws/taboos against employee IQ testing, sustain a comically messy and tragically expensive employment screening method. If the latter was true Murray could still be partially correct: 4 year college could be worthless for the <85th percentile, if employers began to use 20 minutes of psychometric testing, instead of 4 year degrees, as their screening filter.

But, ceteris paribus, college is still the best pay-off.

Labels: education, GSS, IQ

In Obama's unexciting review of the Bell Curve, he remarked:

no one disputes that children whose mothers smoke crack when they're pregnant are going to have developmental problems.

The relevant studies reveal a more complex picture, though. The effects of prenatal cocaine exposure on IQ remain heavily contested to this day. However, recent evidence from Bennett et al points to a 3 to 5 IQ point drop, on average. This is the most recent study on this subject that I'm aware of.

Interestingly, in following with a few previous studies, it was found that boys suffer a greater cognitive loss from prenatal cocaine exposure than girls. Also, the study found that 9 year olds had equally fewer IQ points as their 4 year old counterparts, countering to a certain extent the idea that the IQ loss goes away as development progresses.

If Bennett's numbers are correct, they have small-- but significant-- implications for the Black-White IQ gap. Unlike tobacco and alcohol, which are used by pregnant white and black women at about equal rates and intensities on average*[1], black women are much more[2] likely than white women to use cocaine or crack while pregnant. This is relevant to behavioral genetic studies-- both past and present-- which have aimed to understand the relative contributions of genetics and environment to the IQ gaps. There is no way, as far as I know, to extract prenatal factors like cocaine use from measures of heritability without explicitly measuring such inputs. As far as adoption studies in particular, it stands to reason that women who place their babies up for adoption exceed the rest of the US population in pregnant cocaine use. An interesting thing about the Scarr adoption study is that all of the mothers of the half-black kids were white.

[1] Today, that is. 1989 was the earliest year I could find data for, and in that year the pattern is starkly different from today-- the black-white ratio in fetal alcohol syndrom for this year has way more alcohol use by pregnant black women than pregnant white women, and also much higher rates of fetal alcohol syndrome among black babies. I'm not sure if the rates were comparable in say the 70's, when the Scarr adoption study was performed. That would be interesting data if anyone happens to have it.

[2]~12 times more in the second link, from 1994

*Source for the alcohol/tobacco/fetal alcohol syndrome rates is the CDC.

Labels: IQ

Related: Wayne Allyn Root smarter that Barack Obama?.

Jason's comment deserves promotion so that Google picks it up:

NPR
October 28, 1994
SHOW: All Things Considered (NPR 4:30 pm ET)

Charles Murray's Political Expediency Denounced
BYLINE: BARACK OBAMA
SECTION: News; Domestic
LENGTH: 635 words

HIGHLIGHT: Commentator Barack Obama finds that Charles Murray, author of the controversial "The Bell Curve," demonstrates not scientific expertise but spurious political motivation in his conclusions about race and IQ.

BARACK OBAMA, Commentator: Charles Murray is inviting American down a dangerous path.

NOAH ADAMS, Host: Civil rights lawyer, Barack Obama.

Mr. OBAMA: The idea that inferior genes account for the problems of the poor in general, and blacks in particular, isn't new, of course. Racial supremacists have been using IQ tests to support their theories since the turn of the century. The arguments against such dubious science aren't new either. Scientists have repeatedly told us that genes don't vary much from one race to another, and psychologists have pointed out the role that language and other cultural barriers can play in depressing minority test scores, and no one disputes that children whose mothers smoke crack when they're pregnant are going to have developmental problems.

Now, it shouldn't take a genius to figure out that with early intervention such problems can be prevented. But Mr. Murray isn't interested in prevention. He's interested in pushing a very particular policy agenda, specifically, the elimination of affirmative action and welfare programs aimed at the poor. With one finger out to the political wind, Mr. Murray has apparently decided that white America is ready for a return to good old-fashioned racism so long as it's artfully packaged and can admit for exceptions like Colin Powell. It's easy to see the basis for Mr. Murray's calculations. After watching their income stagnate or decline over the past decade, the majority of Americans are in an ugly mood and deeply resent any advantages, realor perceived, that minorities may enjoy.

I happen to think Mr. Murray's wrong, not just in his estimation of black people, but in his estimation of the broader American public. But I do think Mr. Murray's right about the growing distance between the races. The violence and despair of the inner city are real. So's the problem of street crime. The longer we allow these problems to fester, the easier it becomes for white America to see all blacks as menacing and for black America to see all whites as racist. To close that gap, we're going to have to do more than denounce Mr. Murray's book. We're going to have to take concrete and deliberate action. For blacks, that means taking greater responsibility for the state of our own communities. Too many of us use white racism as an excuse for self-defeating behavior. Too many of our young people think education is a white thing and that the values of hard work and discipline andself-respect are somehow outdated.

That being said, it's time for all of us, and now I'm talking about the larger American community, to acknowledge that we've never even come close to providing equal opportunity to the majority of black children. Real opportunity would mean quality prenatal care for all women and well-funded and innovative public schools for all children. Real opportunity would mean a job at a living wage for everyone who was willing to work, jobs that can return some structure and dignity to people's lives and give inner-city children something more than a basketball rim to shoot for. In the short run, such ladders of opportunity are going to cost more, not less, than either welfare or affirmative action. But, in the long run, our investment should payoff handsomely. That we fail to make this investment is just plain stupid. It's not the result of an intellectual deficit. It's theresult of a moral deficit.

ADAMS: Barack Obama is a civil rights lawyer and writer. He lives in Chicago.

Labels: IQ

Gintis and Bowles have done great work cleaning up a lot of the discussion about cooperation, evolution, and economic outcomes. A Google Scholaring of their names turns up 14 items with over 100 citations, most of which would be well worth reading for GNXP regulars.

But that said, in their 2002 Journal of Economic Perspectives piece "The Inheritance of Inequality," they appear to make a small error. It's an error that's all-too-easy for even good folks to make: They apparently squared the h-squared.

Their big insight and their small error are all part of answering a simple question: How much of the correlation of income between parent and child can be explained by the heritability of IQ? You might think it's straightforward: IQ is highly heritable, so if there's some channel linking IQ to income, then it's all over but the shouting.

But numbers matter. And Gintis/Bowles work out the numbers, finding that there's a weak link in that causal chain: The low correlation (0.27 according to Gintis and Bowles) between IQ and wages. The causal chain goes like this:

1. Parental earnings have a 0.27 correlation with parent's IQ.
2. Heritability of IQ between parent and child is a bit more than 1/2 of h-squared (why a bit more? assortive mating). They take an h-squared of 0.5 for IQ.
3. Child's earnings have a 0.27 correlation with child's IQ.

So the net result is 0.27*0.3*0.27 = 0.022 (page 10). A very small number, especially since the raw parent-child income correlation in U.S. data is about 0.4. So yes, knowing a parent's income helps you predict their adult (especially male) child's income. But only 5% (or 0.022/0.4) of the total correlation can be explained by IQ's impact on wages. Small potatoes.

(Oh, but where's the small error? It's where Gintis and Bowles report that the net result is 0.01 instead of 0.022--a difference that I can most easily attribute to a mistaken squaring of the h-squared.)

If I really wanted to get that net result up from a measly 5%--if I knew in my heart that IQ really was a driving force in intergenerational income inequality--then how would I do it? Well, I might use a higher heritability of IQ, I might assume more assortive mating, or I might assume a bigger correlation between wages and IQ.

Hard to do much to budge that IQ/wage link: Zax and Rees's paper only has a 0.3 correlation between teenage IQ and middle-aged wages, and when Cawley, Heckman et al. regress NLSY wages on the first 10 principal components of the AFQT, they get a similar result.

So you think maybe a higher heritability of IQ will save you? Well, let's just go all the way to perfect heritability of IQ and perfect assortive mating on IQ. In other words, let's see if "IQ clones" will be have enough similarity in wages to match the 0.4 intergenerational correlation of income.

Will the IQ clones have similar incomes? Not so much. (0.3^2)*1 still equals something small: 0.09. Less than 1/4 of the intergeneration correlation in income. Medium-sized potatoes, but we had to make a ton of ridiculous assumptions to get there.

It's that doggone low correlation between IQ and wages, a correlation that has to be squared because we're comparing parent to child. So a high heritability of IQ doesn't imply a high heritability of IQ-caused-income. Another reminder that lots of things impact your wages: Not just how smart you are.

Gintis and Bowles work through some finger exercises to argue for big environmental effects, and that's all well and good. But to my mind, the interesting fact is that income is still highly heritable!

G/B report that MZT (identical twin) earnings correlation is 0.56, and DZT (fraternal twin) earnings correlation is 0.36, so using the crudest of approximations, the heritability of earnings is still (0.56-0.36)*2=0.4. So income apparently has a modestly high heritability, but most of it can't be explained by the IQ-wage channel. Looks like the genetic heritability of income is being driven mostly by non-IQ channels.

Labels: Behavior Genetics, Economics, IQ

In the post below, Colder climates favor civilization even among Whites alone, I made a few comments about possible differences between Germans in Illinois and Germans in Texas, based on nothing much more than a hunch. I trust my hunches, but there's no reason you should, so I decided to see if there was anything here in regards to my assumption about interregional differences in intelligence and how they might track across ethnic groups. So of course I went to the GSS website, and checked the mean WORDSUM scores of various white ethnic groups broken down by region. I specifically focused on whites who stated that their ancestors were from England & Wales, Germany and Ireland. My reasoning is that these are three groups with very large N's within the GSS sample and they are well represented across the regions in absolute numbers. My main motivation was see if the differences across regions were similar for all three groups. Here are the states for each region (the Census made up these categories):

New England - Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, Connecticut
Middle Atlantic - New York, New Jersey, Pennsylvania
East North Central - Ohio, Indiana, Illinois, Michigan, Wisconsin
West North Central - Minnesota, Iowa, Missouri, North Dakota, South Dakota, Nebraska, Kansas
South Atlantic - Delaware, Maryland, District of Columbia, Virginia, West Virginia, North Carolina, South Carolina, Georgia, Florida
East South Central - Kentucky, Tennessee, Alabama, Mississippi
West South Central - Arkansas, Louisiana, Oklahoma, Texas
Mountain - Montana, Idaho, Wyoming, Colorado, New Mexico, Arizona, Utah, Nevada
Pacific - Washington, Oregon, California, Alaska, Hawaii

Obviously the breakdown isn't ideal. I think Delaware and Maryland arguably should be Mid-Atlantic. I also believe that Wisconsin is more plausibly in the West North Central than Missouri or Kansas is. But those are the regional breakdowns and I can't do anything about them.

So, WORDSUM is a vocabulary test on a 0-10 scale. For the whole GSS sample the mean was 6.00, with 1 standard deviation being 2.16. Below is a chart which shows the relationship between WORDSUM scores (Y axis) for various regions (X axis) for each of the three ethnic groups:





The tables below are pretty self-explanatory. At the top you see the mean WORDSUM scores for each ethnic group for each region. I put the N's in there as well so you can see that the sample sizes were pretty big. Note that there is more interregional variation within an ethnic group than there is interethnic variation within a region (the standard deviation across the columns is 50% bigger than across the rows). Just to be clear, I also included some tables which show the differences in WORDSUM mean scores between the regions like so: (row - column) = value.

	New England	Middle Atlantic	East North Central	West North Central	South Atlantic	East South Central	West South Central	Mountain	Pacific	N
England & Wales	7.4	7.09	6.71	6.65	6.66	6.2	6.87	6.84	7.1	2,462
Germany	7.7	6.31	6.01	6.33	6.16	5.83	6.2	6.37	6.36	3,316
Ireland	6.98	7.07	6.15	6.46	6.06	5.66	6.03	6.51	6.88	2,207
England & Wales
	New England	Middle Atlantic	East North Central	West North Central	South Atlantic	East South Central	West South Central	Mountain	Pacific
New England	-	0.31	0.69	0.75	0.74	1.2	0.53	0.56	0.3
Middle Atlantic	-	-	0.38	0.44	0.43	0.89	0.22	0.25	-0.01
East North Central	-	-	-	0.06	0.05	0.51	-0.16	-0.13	-0.39
West North Central	-	-	-	-	-0.01	0.45	-0.22	-0.19	-0.45
South Atlantic	-	-	-	-	-	0.46	-0.21	-0.18	-0.44
East South Central	-	-	-	-	-	-	-0.67	-0.64	-0.9
West South Central	-	-	-	-	-	-	-	0.03	-0.23
Mountain	-	-	-	-	-	-	-	-	-0.26
Pacific	-	-	-	-	-	-	-	-	-
Germany	New England	Middle Atlantic	East North Central	West North Central	South Atlantic	East South Central	West South Central	Mountain	Pacific
New England	-	1.39	1.69	1.37	1.54	1.87	1.5	1.33	1.34
Middle Atlantic	-	-	0.3	-0.02	0.15	0.48	0.11	-0.06	-0.05
East North Central	-	-	-	-0.32	-0.15	0.18	-0.19	-0.36	-0.35
West North Central	-	-	-	-	0.17	0.5	0.13	-0.04	-0.03
South Atlantic	-	-	-	-	-	0.33	-0.04	-0.21	-0.2
East South Central	-	-	-	-	-	-	-0.37	-0.54	-0.53
West South Central	-	-	-	-	-	-	-	-0.17	-0.16
Mountain	-	-	-	-	-	-	-	-	0.01
Pacific	-	-	-	-	-	-	-	-	-
Ireland	New England	Middle Atlantic	East North Central	West North Central	South Atlantic	East South Central	West South Central	Mountain	Pacific
New England	-	-0.09	0.83	0.52	0.92	1.32	0.95	0.47	0.1
Middle Atlantic	-	-	0.92	0.61	1.01	1.41	1.04	0.56	0.19
East North Central	-	-	-	-0.31	0.09	0.49	0.12	-0.36	-0.73
West North Central	-	-	-	-	0.4	0.8	0.43	-0.05	-0.42
South Atlantic	-	-	-	-	-	0.4	0.03	-0.45	-0.82
East South Central	-	-	-	-	-	-	-0.37	-0.85	-1.22
West South Central	-	-	-	-	-	-	-	-0.48	-0.85
Mountain	-	-	-	-	-	-	-	-	-0.37
Pacific	-	-	-	-	-	-	-	-	-

Labels: civilization, climate, crime, education, GSS, IQ, true redneck stereotypes

Last year I had a crazy idea about how winged insects might influence civilization. I only pointed to winged insects as an exemplar, not to suggest a "Mosquito Theory of History" or something stupid and sexy like that. The reasoning is simple: insects are more likely to be winged in certain climates, and that means more effective vectors of disease in such environments; and a greater disease burden makes you dumber, more tired, and more irritable, which stunts the growth of civilization. [1] A qualitative follow-up post looked at where civilizations have ever appeared, and in what climate types they existed.

Well, now I've done some quantitative work, and it turns out that I was right. One critique against an international study is that natural selection may have adapted people to be more or less civilized in different environments, so that the only influence of climate is as a selection pressure for genetic change. There are at least two such studies already out there: one by Templer & Arikawa (2006) and another by Vanhanen (2004). I'm arguing that it matters even when people start out pretty much the same genetically, so I will look just at the US. It varies enough in climate and degree of civilization that any correlation should jump out.

Motivation

In particular, I will look at the correlation, on the level of states, between average annual temperature and the average IQ of Whites, post-secondary degrees awarded to Whites per capita, and the percent of the White population that's imprisoned. I only look at Whites in order to avoid the confound of climate with racial composition (for example, the cold Mountain states are heavily White, while Blacks make up a larger fraction in the hot Southeast).

The reason I look at basic measures like IQ or being in jail, as opposed to the loftier things we associate with civilization, is that smarts is the key determinant of propelling the institutions of civilization forward, while crime gives us a good rough idea of how barbaric we are on a personal level. I'm sure that governments can improve or screw things up too, but it's the raw cognitive and behavioral materials that matter most, as Lynn and Varhanen show in IQ and the Wealth of Nations (see all GNXP posts on this topic). Moreover, studies of representative samples of the population always show a strong influence of IQ on how cultured a person is. See, for example, a National Endowment for the Arts report on the demographics of arts attendees (PDF p. 19), which shows that attendance increases nearly monotonically by education level.

The results







As you can see, hotter average temperature is associated with lower White IQs, fewer degrees being awarded to Whites per capita, and a higher percentage of the White population being imprisoned. The relationship looks pretty linear in each case, and the data are on an interval scale, so we check the Pearson correlation coefficient: between White IQ and temperature, it is -0.48 (p = 0.0005, two-tailed); between degrees to Whites and temperature, it is -0.57 (p = 0.00002, two-tailed); and between percent of Whites in jail and temperature, it is +.40 (p = 0.005, two-tailed). Even conservatively correcting for three independent hypotheses still leaves all results significant (and IQ and getting a college degree are not even independent). At any rate, average temperature accounts for 23%, 32%, and 16% of the variance in White IQ, degrees to Whites, and percent of Whites in jail, respectively -- pretty damn good for social science. [2]

Methods

I took the average annual temperature for each of the 48 continental states (Alaska and Hawaii were not included in the source, so I left them out). Next, I used Audacious Epigone's estimates of White IQ by state, which are based on NAEP data from 8th grade math and science test scores (read about his methods here). I turned to Statemaster.com for the per capita number of post-secondary degrees awarded to Whites. For the number of Whites in prison per 100K Whites in the state's population, I used the data from 1997 in a study by the National Center on Institutions and Alternatives (PDF here), which separates non-Hispanic Whites from Hispanics, unlike most crime data from government agencies. [3]

Discussion

Here, correlation probably is causation, as climate precedes the other three variables in causality, and again because these are unlikely to be genetic differences that reflect adaptation to different environments -- one of the few cases where natural selection "has not had enough time."

An objection is that the differences could reflect a "brain drain," whereby smart people flock to colder states, and their smart children boost the state's NAEP scores. Even in this case, where climate does not cause group differences in IQ, it still confirms the hypothesis that colder climates favor civilization -- why else would smarties flock there? But I doubt this anyway, since Montana, Wyoming, and North and South Dakota are not exactly fonts of civilization that smarties pour into, yet they have White IQs on par with the highly developed New York City metro area.

If it is causation, as seems likely, the mechanism could be anything. Pathogen load is surely part of it, hence the fields of study called "tropical disease" and "tropical medicine." Also, you might sweat too much in hotter environments, bringing you closer to dehydration. As mild as these effects may seem, when accumulated over the course of development, they could result in your body spending more resources on bodily maintenance than on luxury items like IQ and toil. Heat could also just make you more fatigued -- that wouldn't affect IQ, but it would affect your work ethic, making you less likely to complete college and more likely to pursue quick fixes like crime to get what you want.

The correlation is stronger for getting a college degree than performance on 8th grade math and science tests, and that could be because college work is more g-loaded, because it also taps into work ethic aside from IQ, and because out-of-staters show up in the college figures but not the 8th grade figures. As tough as the environment may seem to natives, it must seem unbearable to college students raised in a different climate.

To the best of my knowledge, as the saying goes, this is the first demonstration of an association between climate type and IQ, civilization-related achievement, and crime, even among a population that's pretty homogenous genetically (for the traits of interest, at least). Even what genetic diversity there is among Whites would underestimate the effect -- Whites adapted to hotter environments, such as Italians and Greeks, are far more concentrated in the colder states within the US. To put the final nail in the coffin, though, you'd want to look at babies of Whites who are adopted into White families in a state of noticeably different temperature than that of the biological parents.

Still, it seems pretty unavoidable: hotter environments are less conducive to civilization, at least for Whites, and not just in extreme cases like the failed attempt to colonize sub-Saharan Africa. Civilization may have started in hot areas, but that was then. It apparently flourishes much more in colder climates. Just as we provide iodine in table salt to prevent a nutrient deficiency from lowering IQ, it might be just as well to encourage people to settle colder areas.

It's not like they'd be abandoning civilization -- just the opposite. They could take their accents, music, and whatever else with them, but they would not suffer the environmental insults that lower their group's IQ, lower their ability to get a college degree, and make them more likely to commit crime. Fortunately for them -- and unfortunately for current residents -- the Mountain states have incredibly low population densities and could absorb some Whites from hotter states. That would certainly burden the locals for a generation, but again since lower White IQ in the Southeast is probably due to largely treatable environmental causes, it won't take long for them to contribute as citizens on the same level as the locals.

Notes

[1] Underlying this is likely a tendency for all sorts of things to be more migratory in such environments -- winged insects were chosen because there's lots of solid data to illustrate the point. Basically, environments that are highly unstable favor migratory features since your environment may go from good to bad from one day to the next, or from one spot to the next -- and being able to quickly move on to greener pastures will be well worth it. When environmental quality does not change much in space or time, then the expensive wings (or whatever) will not pay off.

[2] If you don't have statistical software, you can do a lot for free on Wessa.net, including correlation.

[3] Although I didn't run a test of normality on the distributions for temperature, iq, degrees, or crime, I did check the skewness of all, and only crime was significantly skewed: for crime, skewness is +2.1 standard errors of skewness (SES); for temperature, +1.24 SES; for degrees, +0.35 SES; and for IQ, -1.51 SES.

Addendum from Razib: I put up a related post at my other weblog.

Labels: civilization, climate, crime, education, IQ, true redneck stereotypes

Asian-White IQ variance from PISA results:

The NE Asians performed about .5 SD better on average (consistent with IQ test results), and exhibited similar (slightly higher) variance.

Interestingly, the Finns performed quite well on the exam, posting a very high average, but their SD is slightly smaller. The usual arguments about a (slightly) "narrow bell curve" might apply to the Finns, but apparently not to the NE Asians.

Read the whole post to see if you follow the logic of the inferences; I've done some digging on this before to spot check the Europeans-higher-variance meme and didn't find much to support it, and some data to disprove it (though you could explain away that data because of clumping of distinct populations, etc.). That's the main reason I get irritable whenever this meme pops up in the comments, it's one of those "facts" which exhibits circular citation dynamics and spreads like wildfire. Of course, it isn't as if the meme is totally emerging out of a vacuum: if East Asians are so smart why aren't they as scientifically creative??? It seems to me that the most plausible explanation has to be that individual intelligence isn't sufficient for intellectual creativity, though it is likely a necessary precondition. Some of the other variables might be rooted in individual psychology (personality), but I suspect others manifest on a larger scale (e.g., the top-down paternalism and emphasis on conformity which is the norm in most East Asia societies).

Labels: human biodiversity, IQ

Readers in the UK may have seen recent press reports about a controversial article by Bruce Charlton, an evolutionary psychologist at the University of Newcastle. Charlton points out that average IQ differs in different social or occupational classes (e.g. doctors or lawyers have higher IQ than casual labourers), and that in consequence, if IQ is relevant to higher education, we would expect participation in higher education also to vary according to class. Predictably, ritual curses and denunciations have rained down on Charlton's head.

I wanted to read Charlton's article, but found it more difficult to find than I expected. The press reports suggested that it appeared in Times Higher Education (the former Times Higher Educational Supplement), but on tracking down the relevant issue I found a report about Charlton's article, but not the article itself. The article is however available as a Word document on the THE website. (See the right margin of the webpage here). I make a few comments of my own below the fold.


Probably most readers will agree with the broad thrust of Charlton's article, but there may be a confusion between the IQ of parents and that of their offspring. Charlton seems (as far as I can see) to assume that the mean IQ of applicants to higher education is the same as that of adults in their parental social class. This is not generally the case. The correlation between the IQ of parents and offspring is only about .5, which implies considerable regression towards the mean. The IQ of the offspring of parents with IQ of, say, 130 will on average be lower than 130, while that of parents with IQ of, say, 85 will be higher than 85. There is a difference of up to 40 IQ points between adults in the highest and lowest occupational classes (depending on the classification used), but only about 15 to 20 points between children from those classes. (For some data see Anastasi, chapter 15.) The difference in average IQ between social classes is kept roughly constant by social mobility, as the dimmer children of the higher classes tend to fall in the social scale and the brighter children of the lower classes tend to rise. (See Mackintosh, pp. 144-8). This does not invalidate the main point of Charlton's article, but it may affect some of his specific quantitative comparisons.

I think it may also be unfortunate that Charlton describes the present system of entry to higher education as 'meritocratic'. Entry to publicly funded higher education should not be seen (primarily) as a reward for past achievement, or a badge of 'merit'. The proper criterion for entry decisions is how far an individual can benefit from the course of study concerned. In general, individuals who have struggled at school are unlikely to benefit from higher education at all. If applications for a particular course of study exceed the number of places available, those applicants should be chosen who will benefit most from the use of scarce resources. It is the scarcity of high quality resources that justifies the selectivity of the 'elite' universities. One would not expect an haute couture seamstress to stitch potato sacks, and one should not expect a Fellow of Trinity College Cambridge to teach mediocre students. Such students would not derive the greatest benefit from the teaching, and indeed the teaching would probably not be the best available for such students.

I am assuming in all this that higher education is by definition at a more advanced and demanding level than that of ordinary school education. It is not to be confused with post-school education at a similar level to that of schools, such as is provided by Further Education Colleges in Britain. This may be admirable in its own way, but it is not higher education.

References:
Anne Anastasi: Differential Psychology, 3rd edn., 1958
N. J. Mackintosh: IQ and Human Intelligence, 1998

Labels: education, IQ

A study on the correlation between IL1RAPL1 and human cognitive ability:

This study aimed to investigate the effects of IL1RAPL1 on the human cognitive ability...Results indicated that genotypes of DXS1218, DXS9896 and rs12847959 were associated with memory/concentration factor intelligence quotient (IQ)...DXS1218 also associated with full IQ, verbal IQ, and performance IQ...rs12847959 were related to verbal comprehension factor and perceptual organization factor IQ...Further study on rat brain revealed that Il1rapl was mainly expressed in memory/concentration-associated encephalic regions, such as hippocampus, dentate fascia, osmesis perithelium, and piriform cortex. mRNA expression levels of Il1rapl in brains of rats with different learning and memory abilities showed significant difference. Combined data suggested that IL1RAPL1 affected human cognitive ability to some extent, especially the memory and concentration capability.

Check out the HapMap on that SNP. Remember to wait up on reproducibility here. Sandy has a longer post addressing the radioactivity of such research (obviously he is lying when he says he's an anthropologist; doesn't pass the smell test).

Labels: Genetics, IQ

Just got a note from someone I trust that a massive QTL for IQ has been discovered, on the order of 10 points in effect for a substitution of the the major allele for the minor (it's additive and independent, so homozygote minor allele ~ 20 points greater than homozygote major allele). The novel variant is found in an ethnic-religious minority population and no other phenotypic effects are discernble for those who carry the IQ boosting polymorphism. Everything is very preliminary at this point...but they've checked and re-checked and this seems to be real. There are two genes previous implicated in neurological pathologies in this region of the genome, so a molecular genetic & physiological story should be easy to extract.

I'm being a little vague on the details for obvious reasons; no one wants to be scooped. But word is spreading through the labs though, so my friend thought it might be good to prep the public and those at GNXP who are interested in this topic. Expect a Nick Wade article as soon as possible. Exciting times....

Update: Yes, April Fool's. Obviously I wasn't going to do something like taking down the site and pretending someone was going to sue us; you might recall that several GNXP readers sent the befuddled sysop of the Gene Expression Omnibus some irate emails....

Labels: human biodiversity, IQ

Over at The American Scene Jim Manzi has an interesting post.

Labels: IQ

Mark Liberman at Language Log (a blog which I very much enjoy, I should point out) approvingly links to Cosma Shalizi's rant against Slate for publishing a series of articles on race and IQ. His conclusion:

So to start with, you should ask yourself whether you can define and calculate the variance of a set of numbers, or the correlation between two sequenccs of numbers. If not, then read the (linked) wikipedia articles -- and spend a little time playing with the concepts in the context of an interactive program like R. Once you've paid that entry fee, read Cosma's posts. (It's more fun that you might think -- I especially recommend the discussion of the heritability of zip codes, and you could go back and read the prequel about the heritability of accent.) And then go through William Saletan's articles, and decide for yourself what they mean about the abilities and motivations of the writer and his editors.

It's amazing how quickly people go from simple disagreement to armchair psychologist mode; a little perspective is in order here.

Dr. Liberman assumes that Cosma concludes that heritability estimates are worthless. This is not the case. Cosma points out that estimating heritability involves making assumptions that are often incorrect, but (I feel like I've said this many times before) all models are wrong, but some are useful. And buried in his prose (which contains many important, ill-understood points about the estimation of heritability), he cites a nice paper on the heritability of IQ, which concludes for a narrow-sense heritability of ~0.34 (that is, additive genetic factors account for ~34% of the variance in IQ, see the linked post). Cosma wants to add additional parameters to this model before he makes any definitive statements, but he can't bring himself to treat IQ differently than other traits:

If you put a gun to my head and asked me to guess [whether there are genetic variants that contribute to IQ], and I couldn't tell what answer you wanted to hear, I'd say that my suspicion is that there are, mostly on the strength of analogy to other areas of biology where we know much more. I would then - cautiously, because you have a gun to my head - suggest that you read, say, Dobzhansky on the distinction between "human equality" and "genetic identity", and ask why it is so important to you that IQ be heritable and unchangeable.

So if he had to guess, there is probably a genetic component to IQ, environment also plays a role, and human equality is not dependent on genetic identity. Seriously, read Saletan's column--these are exactly his points!

Referring back to my point about the utility of incorrect models, it's worth noting that, if you don't accept any of the heritability estimates proposed in humans, you're rejecting that any trait could be determined to have a genetic component before, oh, 2001. I don't think that's a good idea, and here's why: the heritability of type II diabetes was estimated at a "mere" 0.25 (using all those horribly flawed methods, and including, since it is a dichotomous trait, even more assumptions); now molecular studies have identified at least 9 loci involved in the disease. The heritability of Type I diabetes was estimated at about 0.88; now, there are 10 loci undoubtably associated with the disease. There are other examples, and more sure to come, but suffice it to say that heritability studies, with all their seemingly ridiculous assumptions, are not worthless.

Now look to Cosma's post on g. Again, this time in the footnotes, we see something in line with Saletan's article. Referring to the observation by economist Tyler Cowen that some people he knew in a village in Mexico were smart in ways not measureable by IQ tests, he writes:

Cowen points out behaviors which call for intelligence, in the ordinary meaning of the word, and that these intelligent people would score badly on IQ tests. A reasonable counter-argument would be something like: "It's true that 'intelligence', in the ordinary sense, is a very broad and imprecise concept, and it's not surprising the tests don't capture it perfectly. But the aspects of 'intelligence' they do capture are ones which are vastly more important for economic development than the ones displayed by Cowen's friends in San Agustin Oapan, however amiable or even admirable those traits might be in their own right." This would be a position about which one could have a rational argument. (Indeed, I might even agree with that statement, as far as it goes, as might A. R. Luria.)

So Cosma "might" agree that intelligence, as operationally defined by psychologists, is important for economic development and differs in distribution between groups. Interesting.

Cosma's posts seem to follow any discussion of IQ around in the "blogosphere". They're well-written, include legitimate discussion of many important issues in quantitative genetics and IQ testing (ok, I don't know much about IQ testing, but I'm assured this is the case by people who do), and come from an authority. But for whatever reason (I'm tempted to think that people don't actually read what he writes. I mean, it has, like, math and stuff), he's interpreted as saying that intelligence tests and the concept of heritability are entirely meaningless. That is not the case.

Labels: Genetics, IQ, Statistics

Razib noted, in his post on the IQ-breastfeeding-FADS2 story, that it reminded him of research on MAOA. There's a reason: it's by the same group. In fact, the IQ study is the third in a "trifecta" of gene-environment interactions postulated by Avshalom Caspi and colleagues. Curious about whether their statistical methods were similar in all these studies, I went back to them.

1. In 2002, the authors reported an interaction between variation in MAOA and childhood maltreatment on the probability of developing "antisocial problems". The relevant graph is on the right. It's important to keep in mind, from a statistical standpoint, what an interaction is: in a regression of variable Y on variable X, if the slope of the line significantly differs depending on another variable Z, one concludes for an interaction between Z and X. In this, the slopes do appear to be different, and the authors find this is indeed statistically supported. They don't include parental "antisocial behavior" as a covariate in their regression, either because they don't have that data or didn't think to include it.

2. In 2003, the authors then genotyped another locus in the cohort studied above, this time the serotonin transporter. They reported a significant interaction between polymorphism in this gene and stressful life events on risk of depression. Again the relevant graphs are on the right. Across several measures of depression, there does appear to be an interaction. Again, no inclusion of parental phenotype in the regression.

3. Now let's consider the IQ-FADS2 story. Again, they use the same cohort (as well as a replication cohort). This time, instead of genotyping known functional variants in a gene thought to be involved in the phenotype, they genotype a couple tagging SNPs in a gene picked through some spectacular logical leaps (1. there is a link between breastfeeding and IQ. 2. That link is modulted through fatty acid metabolism. 3. Of all the genes involved in fatty acid metabolism, the one of interest is FADS2). This has to change your priors on whether anything they find is real. Again, check the graph on the right: this time, they don't have the nice dose-response curve that they had in the others, so they go for a bar chart. And it does indeed look a little noiser. The replication, though, is something that wasn't present in the other studies.

The fact that they have a measure of maternal IQ but don't directly include it in the published multiple regression suggests that they tried it, but didn't like the results. They didn't include parental phenotype in any of their previous studies, but there, at least, there was some functional evidence linking the polymorphism and the phenotype. Here, there's nothing. Considering the fact mentioned in a previous post that other researchers find absolutely no evidence for link between IQ and breastfeeding (the entire basis for this study), this has to be classified as highly questionable. And regardless of the veracity of any gene-environment interactions here, the huge effects of breastfeeding on IQ shown by the authors are clearly artefacts of the heritability of IQ, and it's unfortunate that they are being propogated.

Half Sigma is apoplectic about this; I'm not so much-- this is a case of researchers having a hammer (their cohort and a desire to find gene-environment interactions), and seeing every problem as a nail, not some ode to breast-feeding.

Anyways, on a completely unrelated note, here's small nugget from their Supplementary Table 2, where they break down IQ by social class. I suppose I'd seen figures like this before (ie. in The Bell Curve), but it still gave me a start:

Low class: 93.5 (11.6)
Middle class: 100.5 (13.7)
High class: 111.4 (12.8)

In parentheses are standard deviations.

Labels: Genetics, IQ

In an interesting story on the relationship between teen delinquency and sex (long story short: people who concluded early sex caused delinquency unsurprisingly failed to control for genetics and were led astray) I saw this little bit:

A recent study by Scottish researchers asked whether the higher IQs seen in breast-fed children are the result of the breast milk they got or some other factor. By comparing the IQs of sibling pairs in which one was breast-fed and the other not, it found that breast milk is irrelevant to IQ and that the mother's IQ explains both the decision to breast-feed and her children's IQ.

Now, this is interesting in light of the recent study claiming to find a gene-environment interaction between breast-feeding and a particular gene. The source for the claim that breast-feeding has no effect on IQ is here. I went back and looked at the recent paper's attempts at controlling for maternal IQ. Statstically, this is not a difficult thing to do-- a linear regression of child IQ on maternal IQ, breast feeding status and genotype can easily be compared with a model that includes a breast feeding staus X genotype interaction.

The authors don't do this standard analysis, however--they only include a cryptic note explaining that there is no significant "interaction" between the SNP in question and maternal IQ. It's not the interaction term that's interesting, of course; it's whether the marginal effect of maternal IQ removes their already tenuous claims of an interaction between breast feeding and genotype. One gets the distinct feeling that some unfavorable results are being swept under the rug. Combine this, plus the study above, then add your prior probability that by genotyping two (2!) SNPs in the entire genome you'll find a real gene-environment interaction, and, well, it's not a stretch to say the authors haven't quite demonstrated what they think they have.

Labels: Genetics, IQ, Statistics

The current issue of CATO Unbound is about IQ. James Flynn has already put something up, Linda Gottfredson, Stephen Ceci and Eric Turkheimer on deck.

Labels: IQ, Psychology

Read it here.

Update: Eye on DNA has much more.

Jason M. adds: In the comments HapMap Jockey Marc again applies the wisdom from p-ter's HapMap How-2 to the latest IQ genes:

In the study itself, there were two cohorts: a British cohort and a New Zealand cohort. In both cohorts, presence of the C allele (as either CC or CG) was associated with a hike in IQ by 6.4 and 7.0 points (from around 99-100 to around 106) in the two samples. But those without the C allele (GG) had mean IQs of 99.5 in Britain and 100.3 in New Zealand.

Incidentally, I plugged rs174575 into the ol' Hapmap, and it seems that the C allele has a frequency rate of 72% among Utah whites, 73% among Yorubans, 89% among the Chinese, and 90% among the Japanese.

Assuming these numbers are representative, universal breastfeeding alone would lead to a gap of 1.12 to 1.225 in IQs between East Asians and whites, favoring East Asians.

On the other hand, since whites and blacks have nearly the same C allele frequency (assuming, again that these numbers are representative of white and black populations), but whites breastfeed their babies at higher rates than blacks (60% vs. 30%, according to Steve), this is pretty solid evidence that increasing the percentage of black women who breastfeed their children will have a diminishing effect on the black white IQ gap.

Since I'm already blowing off work (damn you, Gene Expression!) I might as well do the calculations. Let's see... The 30% difference in breastfeeding is responsible for between 1.4 and 1.53 points in the black-white IQ gap! (I got these figures by multiplying the frequency rate of the C allele in Yorubans with the percentage difference in breastfeeding between blacks and whites with the effects of breastfeeding on the IQs of C allele carriers.)

Steve Sailer is vindicated!

Additional props to Rob in the comments at FuturePundit.

Labels: Behavior Genetics, IQ

Cosma Shalizi has put up a gigantic post on IQ & heritability; he originally titled it "Duet for Leo and Razib," implying that I, and the audience here @ Gene Expression, are the targets of his eloquence (at least in part). Now, I have to admit something, I'm not really interested in psychometrics that much anymore. It has been a while since I have been, stupid people are obviously stupid and I am not interesting in debating that fact. I take my own opinions in this area as background assumptions, so I'm not going to respond to Cosma. In fact, I won't read the post right now, there's some interesting stuff on HLA & heterozygosity that I want to check out! But, I do invite readers to digest what Cosma is saying, because I guarantee you that you'll see it replicated by lesser minds elsewhere.

Labels: human biodiversity, IQ

I posted recently on the Flynn Effect, and some interesting papers on the subject came to my attention afterwards.

First, there is a review of Flynn's recent book by Richard Lynn in Intelligence, 2007, (35), 515-16. Lynn defends his own nutritional explanation of the Flynn Effect against various criticisms. He points out that it is one of the few theories that can explain an increase in IQ among young children.

A more substantial piece was mentioned in comments on my post. For several years M. Mingroni has been arguing that heterosis ('hybrid vigor') has played a major part in the Flynn Effect. This makes him unusual in proposing a mainly genetic, rather than environmental, explanation. His latest paper is in Psychological Review, 2007, 114(3), 806-29. An abstract is available here.

The first part of the paper criticises existing explanations such as nutrition, schooling, etc. Mingroni makes some good points, but I think that he and some others make the mistake of assuming that there has to be a single, or at least a main, explanation of the Flynn Effect. If the Flynn Effect were substantially uniform across all tests, all age groups, all countries, etc, this would be a reasonable assumption, but it isn't that uniform. There is no more reason to expect to find a single explanation of rising IQ scores than of rising life expectancy. The Flynn Effect might be due to a bit of nutrition, a bit of schooling, a bit of heterosis, a bit of audiovisual stimulation, and other factors, in various proportions in different times, places, and age groups. I'm all in favour of simple explanations where they work, but we should not always expect them to.

[Added on 24 September: Of course, all the various suggested factors - nutrition, schooling, heterosis, etc - are ultimately due to economic growth, but it would not be helpful to identify 'economic growth' as the 'cause' of the Flynn Effect, any more than of increasing life expectancy. We want something more specific. ]

The second part of Mingroni's paper is more constructive, and sets out a model for examining the effects of heterosis. I discuss it further below the fold, but I should stress now that Mingroni does not prove (or even claim to prove) that heterosis accounts for a large part of the Flynn Effect. Using plausible parameters his model only accounts for an increase of 2 to 5 points in mean IQ, which is less than a quarter of the cumulative Flynn Effect.



The possibility of heterosis increasing IQ scores is not controversial. Close inbreeding (e.g. cousin marriage) usually reduces the IQ of the offspring. This suggests that some genes for low IQ are recessive. Conversely, genes for higher IQ are probably often dominant. If so, then for any given set of underlying gene frequencies in the population, the mean IQ will be higher when the proportion of heterozygotes is higher. Random mating will therefore produce higher mean IQ than inbreeding, which for this purpose includes not only inbreeding in the traditional sense, but also breeding confined within subpopulations. If gene frequencies within such subpopulations vary, then the proportion of homozygotes will on average be higher than if the subpopulations were merged together in a random-mating total population.

If subpopulations are geographically or otherwise isolated from each other, they will evolve differing gene frequencies as a result of genetic drift or differential selective pressures. Over the last few centuries the population structure in many countries has changed in such a way as to break down such isolation. Small communities have been absorbed into larger towns, much of the rural population has migrated into cities, and improved transport has mixed up populations within the same countries and even internationally.

It is therefore reasonable to hypothesise that heterosis has made some contribution to the Flynn Effect. The question is how much. Mingroni's paper develops a model to explore this question. I can only give a rough outline here. It is assumed that a large number of loci affect IQ, with two alleles at each locus. The population is assumed to be initially subdivided and then merged into a single random-mating population. The variable quantities are the number of loci, the degree of dominance, the frequency of each allele in the total population, and the amount of increase in heterozygosity assumed to take place as a result of changing population structure. Values are assigned to genotypes in accordance with the degree of dominance, and gene frequencies for each allele are assigned stochastically to each locus within the subpopulations. The initial mean and standard deviation of IQ in the population resulting from the model is calculated and scaled to have a mean of 100 and s.d. of 15. The effect of the postulated change in heterozygosity on the mean and s.d. of IQ is then derived for a range of values for the key variables.

The choice of values is determined in part by plausibility and in part by empirical data. It is assumed that the number of relevant loci is either 50, 75 or 100. The dominant homozygote has the value 1, the recessive homozygote has the value 0, and the heterozygote has the value .6, .8 or 1 according to the degree of dominance. The population frequency of the recessive allele at each locus is either .4, .5, or .6. The increase in heterozygosity resulting from merging the subpopulations is either .02, .03, or .04; that is, between 2 and 4 percent. (These figures are based largely on Cavalli-Sforza's classic studies on isolated Italian villages in the late 1950s.)

With these assumptions Mingroni obtains increases in mean IQ ranging between 1.2 and 5.1 IQ points, with most results falling between 2 and 4 points. These changes are much smaller than the observed cumulative Flynn Effect, but Mingroni argues that the total change in heterozygosity at a national level might be much larger than those suggested by the Italian data. Opinions will differ on the plausibility of this. Personally, I would be sceptical. Cavalli-Sforza chose his Italian villages to represent a relatively isolated pattern of settlement and marriage, in order to give genetic drift a chance to show itself. I doubt that the traditional degree of isolation would be as large as this in many parts of Europe. (The degree of inbreeding might be higher in some non-European societies, especially where cousin-marriage is common.)

It is possible to calculate the initial difference in allele frequencies needed to produce a given increase in heterozygosity when the subpopulations are merged. For two equal subpopulations, and two alleles at a locus, the increase in heterozygosity produced by merging the subpopulations, as a percentage of the population, is (D^2)/2, where D is the difference in allele frequencies between the subpopulations. [Note] To produce an increase greater than Mingroni's upper figure of 4 percent the differences between subpopulations have to be quite large, e.g. a difference of around 30 percent in allele frequencies. This is larger than the usual differences between European nations, let alone different parts of the same nation. If there are more than two alleles the differences in allele frequencies have to be even larger. For example, if the subpopulations have 3 alleles at a locus, with frequencies of .2, .4, .4 in one subpopulation, and .1, .6, and .3 in the other (an aggregate difference of 40 percent), the effect of merging the subpopulations would only be to increase heterozygosity at the locus from .59 to .605. (If there are more than two subpopulations, a multi-allele system would have more scope, as each allele might be concentrated in a different subpopulation, but the differences in frequency between subpopulations would still have to be large to make much impact.)

In Mingroni's simulations an increase of 1 percent in heterozygosity produces an increase of about 1.1 points in the mean IQ of the population. The increase seems to be linear, as it should be, since each substitution of heterozygotes for homozygotes adds a fixed amount to the total IQ 'score' of the population. A cumulative IQ increase of around 20 points therefore requires an increase in heterozygosity equivalent to around 18 percent of the population. This requires a huge initial difference in allele frequencies - around 60 percent - larger than the usual difference between continents.

I also see a problem with the timing of the changes. In the first countries to industrialise, much of the breakdown in traditional population structure occurred in the 18th and 19th centuries. To take the most obvious example, in Britain some 90% of the population already lived in large towns and cities by the end of the 19th century. The scope for further increases in heterozygosity during the 20th century (excluding interracial mating) must have been quite small. Yet the Flynn Effect has been much the same in Britain as elsewhere.

Then there are those populations founded by immigrants. The best example is perhaps Australia. From the beginning of white settlement around 1800, the population of Australia was drawn from all over the British Isles (and contrary to myth, only a small proportion were convicts). If Mingroni is right in believing that heterosis can account for the bulk of the Flynn Effect, we would expect Australia to have had a spectacular one-off increase in IQ compared with the parent population. I mean no disrespect to Australia if I say that this has not been observed. Much the same argument can be applied to New Zealand and Anglophone Canada. The United States is a more complex case, as settlement extended over a longer period, and involved a variety of European groups who settled to some extent in different areas (Germans in Pennsylvania, Scandinavians in Minnesota, etc.) There could be parts of the United States where populations were quite inbred and the scope for heterosis was correspondingly large. But there must also have been areas (e.g. California and other west coast states) where the white population was well-mixed from the beginning of settlement. This would leave little scope for further IQ gains from heterosis. These are fairly obvious difficulties, but I cannot see that Mingroni addresses them


Note: Suppose the frequency of one allele in the total population is M. The frequency of the other allele is therefore (1 - M). Under random mating in the total population the proportion of heterozygotes will be 1 - M^2 - (1 - M)^2 = 2(M - M^2). Now suppose the population is divided into two equal subpopulations, A and B. If the frequency of one allele in A is (M - d), the frequency of the other allele must be (1 - M + d), while the corresponding frequencies in B are (M + d) and (1 - M - d). Under random mating within each subpopulation the average proportion of heterozygotes will be [1 - (M - d)^2 - (1 - M + d)^2 + 1 - (M + d)^2 - (1 - M -d)^2]/2 = 2(M - M^2 - d^2). This is 2d^2 less than under random mating in the total population. The amount 'd' is here the difference between the frequencies of each allele in the subpopulations and the mean for the total population. The difference in frequency of the same allele between the two subpopulations is 2d. If we set D = 2d, then 2d^2 = (D^2)/2. So it is easy to calculate the increase of heterozygosity (measured as a proportion of the population) resulting from the merger of the subpopulations for a given difference in allele frequencies, and the associated increase of IQ e.g.:

D...........(D^2)/2..........IQ points gain
0.1............0.005...........0.6
0.2............0.02............2.2
0.3............0.045...........5.0
0.4............0.08............8.8
0.5............0.125..........13.8
0.6............0.18...........19.8
0.7............0.245..........27.0

These figures are independent of the value of M, but there are constraints on the possible values of D. E.g. if M is .8, D cannot be greater than .4, since M + D/2 cannot be greater than 1. There are of course many simplifying assumptions, so the figures should not be taken too seriously.

Labels: IQ

In his September 14, 2007 op-ed piece in the New York Times, David Brooks tells his impression of the latest research in cognitive ability. Unfortunately, he not only misses the forest, but he bungles a few trees as well. Article and comments below.

A nice phenomenon of the past few years is the diminishing influence of I.Q.

Right out of the block he is off. In what domain was there once a non-zero IQ-outcome relation, but now, X number of years later, the relation has shown a systematic decrease? From the generality of the statement, one would expect this to hold across most, if not all, pertinent domains (e.g., occupation, academic success, etc.). However, that is not the case. Not only do the IQ-achievement, and IQ-occupation relationships still hold, but now there is a burgeoning new field in the area: cognitive epidemiology, that looks to see how health outcomes are related to cognitive ability. Deary et al give a terse summary here, and Gottfredson gives a conceptual overview here. But, perhaps more interesting, researchers who have no interest in intelligence per se are finding similar results: a case-in-point is Yakov Stern's cognitive reserve research that shows people with higher IQ scores tend to have have less severe symptoms of Alzheimer's symptoms. As this is a new area of inquiry, the exact nature of the relationship has not been identified, but one thing we can say for sure is that there is no diminishing influence of cognitive ability.

For a time, I.Q. was the most reliable method we had to capture mental aptitude. People had the impression that we are born with these information-processing engines in our heads and that smart people have more horsepower than dumb people.

These two statements have little to do with each other. IQ (at least as derived from a Full Scale score) has been, and still is, very reliable for most age groups and subpopulations, no matter how you measure reliability. For example, the Woodcock-Johnson, one of the more theoretically sound measures of cognitive ability, reports in their new normative update that the coefficient alpha values (which are a lower bound of reliability) above .90 for all ages ranging from 3 to over 80. Given that the maximum value alpha can take is 1 (under almost all circumstances), this is pretty good evidence. If you look at the technical manual for the Wechsler, Stanford-Binet, or Reynolds Intellectual Assessment Scales, you'll find very similar values (I refer to these only because their norms span a very large age group, and the full scale score is derived from multiple subtests). I challenge Mr. Brooks to find a more reliably-measured psychological construct in psychology, nay, in the social sciences.

The second statement, while perhaps overstated, is true. People are born with brains, these brains process information, and smarter people (as measured by IQ scores) tend to process information faster (see, for example, here and here). What impression should people have instead? People are born with a blank slate and all of life is little more that the acquisition of stimulus-response patterns? Skinner died in the 1990s, and strict adherence to this view died long before that (a great book about this).

And in fact, there's something to that. There is such a thing as general intelligence; people who are good at one mental skill tend to be good at others. This intelligence is partly hereditary. A meta-analysis by Bernie Devlin of the University of Pittsburgh found that genes account for about 48 percent of the differences in I.Q. scores. There's even evidence that people with bigger brains tend to
have higher intelligence.

No disagreement here.

But there has always been something opaque about I.Q. In the first place, there's no consensus about what intelligence is. Some people think intelligence is the ability to adapt to an environment, others that capacity to think abstractly, and so on.

Ah, the slippery slope begins. These arguments are so old, and well-answered in the literature that it is almost painful to repeat them. I refer the interested (and Mr. Brooks) to Seligman's phenomenal, non-technical introduction, as well as Deary's brilliant literary corpuscle. First, IQ and intelligence are two different things. One is a measuring instrument's scale and the other is a psychological construct that is measured, to one degree or another, by an IQ test. We don't confuse inches and paper, so why do we confuse IQ and intelligence? Second, few scholars actually study intelligence. While the word might be used in common parlance, there is no common definition. Instead, most serious scholars study general intelligence (g) or one of its sub-constructs (e..g, fluid abilities, crystallized abilities; see here or here or here). Once you make the jump to g, the definition becomes much more consensual. There are technical debates (as there are in any branch of science), but it's measurement (by factor analysis of one flavor or another) is virtually undebated. For most purposes in daily life, it is OK to quasi-equate intelligence and g, as well as IQ scores and
intelligence, but they really are quite different concepts.

Then there are weird patterns. For example, over the past century, average I.Q. scores have risen at a rate of about 3 to 6 points per decade. This phenomenon, known as the Flynn effect, has been measured in many countries and across all age groups. Nobody seems to understand why this happens or why it seems to be petering out in some places, like Scandinavia.

IQ scores, across generations, need re-calibrated for valid comparisons. We have ways that do this very well (latent trait models), that have very sound theory behind them. You have to periodically re-calibrate your bathroom scale, and you have no question about what it is measuring; why should IQ be any different? As a side note, this phenomenon is not at all confined to IQ tests, and it has been known about in the psychometric literature for decades, although it is called item parameter drift there. Moreover, just because there is no consensus as to why cross-generational scores tended to rise in the mid-twentieth century, this does nothing to invalidate the validity of interpreting IQ scores within a generation.

I.Q. can also be powerfully affected by environment. As Eric Turkheimer of the University of Virginia and others have shown, growing up in poverty can affect your intelligence for the worse. Growing up in an emotionally strangled household also affects I.Q. One of the classic findings of this was made by H.M. Skeels back in the 1930s. He studied mentally retarded orphans who were put in foster homes. After four years, their I.Q.'s diverged an amazing 50 points from orphans who were not moved. And the remarkable thing is the mothers who adopted the orphans were themselves mentally retarded and living in a different institution. It wasn't tutoring that produced the I.Q. spike; it was love.

Brooks is telling all parents of children who have Mental Retardation or Borderline Intelligence that their children's low cognitive ability is a direct result of parental inadequacy. If these parents would love their children more, the Mental Retardation would go away. If I were king, I would mandate that any person with the gumption to make asinine statements like this do two things (a) read Spitz's chef d'oeuvre, and (b) spend a week with a family who have a child diagnosed with Mental Retardation. Not just a daily visit, but an in vivo experience. Then get back to me about how easy it is raise the cognitive ability of people with mental retardation.

By the way, Turkheimer's studies look at the ability of the environmental variance to modify heritabilty estimates. Specifically, people who grow up in more impoverished environment have a more variable environments, which, almost by definition, decreases heritability estimates. This is a very long cry from showing "growing up in poverty can affect your intelligence for the worse".

Then, finally, there are the various theories of multiple intelligences. We don't just have one thing called intelligence. We have a lot of distinct mental capacities. These theories thrive, despite resistance from the statisticians, because they explain everyday experience. I'm decent at processing words, but when it comes to calculating the caroms on a pool table, I have the aptitude of a sea slug.

What? A few paragraphs ago general intelligence existed, now it doesn't? Anyway, it is an awful shame when everyday experience does not map onto what data tell us: Beth Visser recently (gasp!) gathered data to test Gardner's theory. What did she find? Basically what John Carrol said she would find a decade ago: these multiple intelligence all positively correlate (sans kinesthetic intelligence) and a strong g factor can be extracted when the measures are factor analyzed.

I.Q., in other words, is a black box. It measures something, but it's not clear what it is or whether it's good at predicting how people will do in life. Over the past few years, scientists have opened the black box to investigate the brain itself, not a statistical artifact.

I wish I had the luxury of being able to write blatantly false statements in a national paper. There is over 100 years of empirical literature investigating the construct validity of IQ. There is also 100 years of literature examining what, and how well, IQ scores predict life outcomes. A simple perusing of Jensen's g factor or Brand's g factor (this one is even available for free!) would have sufficed here; but who wants data to interfere with a good opinion?

Now you can read books about mental capacities in which the subject of I.Q. and intelligence barely comes up. The authors are concerned instead with, say, the parallel processes that compete for attention in the brain, and how they integrate. They're discovering that far from being a cold engine for processing information, neural connections are shaped by emotion.

...and you can read books about journalism in which the subject of sophism barely comes up. Namely because the books are concerned about journalism, not logical arguments. Why would a cognitive scientist who is writing a book about attention necessarily include a chapter about intelligence? As a rule, cognitive scientists tend to be concerned with general processes, not individual differences. The field can learn much from each other, but they are concerned about very different areas of investigation.

Antonio Damasio of the University of Southern California had a patient rendered emotionless by damage to his frontal lobes. When asked what day he could come back for an appointment, he stood there for nearly half an hour describing the pros and cons of different dates, but was incapable of making a decision. This is not the Spock-like brain engine suggested by the I.Q.

By all means, lets infer from one person with severe brain damage to the entire population. But if we want to play this game, I had a patient once who had just started Kindergarten, but could do addition, subtraction, multiplication and long division (the latter of which he deduced how to do pretty much on his own). He did not need a school to teach him any of this, so lets get rid of elementary schools for everyone. After all, if my patient could figure out long division, so should every other 5 year old.

Today, the research that dominates public conversation is not about raw brain power but about the strengths and consequences of specific processes. Daniel Schacter of Harvard writes about the vices that flow from the way memory works. Daniel Gilbert, also of Harvard, describes the mistakes people make in perceiving the future. If people at Harvard are moving beyond general intelligence, you know something big is happening.

Harvard never was a bastion for the study of general intelligence. It was the University of London. In fact, except for Yerkes, Herrnstein, and, to some extent, Pinker, I can't think of too many profs. there who contributed much to the study of general intelligence. And since when did Harvard's Psychology department become the measuring stick by which the importance of a research agenda was measured? I'm sure much of the work they do there furthers the general field of psychology, but what makes their research more special than, say, Berkeley, Stanford, UT-Austin, etc.?

The cultural consequence is that judging intelligence is less like measuring horsepower in an engine and more like watching ballet. Speed and strength are part of intelligence, and these things can be measured numerically, but the essence of the activity is found in the rhythm and grace and personality — traits that are the products of an idiosyncratic blend of emotions, experiences, motivations and inheritances.

This paragraph is quite confusing, perhaps due to the mixing of automotive and ballet metaphors. I think Brooks is trying to tell his readers he thinks personality is important for modern culture. I agree. And that has absolutely no bearing on the importance (or lack thereof) of cognitive ability in the same culture.

Recent brain research, rather than reducing everything to electrical impulses and quantifiable pulses, actually enhances our appreciation of human complexity and richness. While psychometrics offered the false allure of objective fact, the new science brings us back into contact with literature, history and the humanities, and, ultimately, to the uniqueness of the individual.

What? First, psychometrics (and specifically, the study of cognitive ability) has always held as paramount the uniqueness of the individual. Second, how has the study of cognitive ability NOT shown the complexity of humanity? Sir Cyril Burt, one of the pioneers in the field, was enamored with the complexity of students he encountered while a school psychologist in London. In fact, he was such an ardent supporter of psychological measurement so that he could begin to quantify, and, ultimately, understand and predict, this variability(see a bibliography here). More modern techniques, such as fMRIs, extend the work of psychometrics, in that they add to our ability to quantify individual variability at a much more precise level. However the two are quite complementary. From here:

Despite the sometimes contentious controversy about whether intelligence can or should be measured, the array of neuroimaging studies reviewed here demonstrates that scores on many psychometrically-based measures of intellectual ability have robust correlates in brain structure and function. Moreover, the consistencies demonstrated among studies further undermine claims that intelligence testing has no empirical basis.

In the world of academia, to have your ideas printed in a reputable journal, you have to go through the peer-review process. While there are arguments for the pros and cons of this process, at least it frequently squashes ill-informed, blatantly false propaganda from reaching the masses. After reading op-ed like this, one wishes the NYT had a similar mechanism in place.

Labels: David Brooks, general intelligence, IQ

Recently I suggested that civilization flourishes in some areas of the world more than others, in part, because winged insects thrive more in environments that are lower in elevation and latitude. These insects are a key source of chronic infectious disease in humans, and having to deal with the recurring symptoms must sap some of your body's resources that could be used for "luxury" processes involved in societal innovation. I neglected to mention that what likely makes wingedness more common in such environments -- a higher degree of environmental heterogeneity -- likely selects for an increase in migratory features more broadly, not just in insects. So some small animal may be more migratory, and it could be carrying parasites or pathogens itself, or be harboring insects that carry pathogens. It's just a lot easier for disease vectors to make their way to you in such environments. And of course, it may be that the fatigue caused by hot, humid weather makes you less productive.

Since then, I looked again at Inductivist's analyses on White IQ in various regions of the US, based on GSS data. In the first two posts (here and here), he showed that adults in the Mountain (MTN) region score better than average on mean IQ and percentage of holders of college degrees. More interesting, though, is the post on IQ and geographical mobility. Although New England and the Mid-Atlantic far and away attract the smartest Whites, the smartest of all are the NE transplants who were raised in MTN. Moreover, none of the bottom 10 pairs consisted of a group that was raised in MTN. By contrast, even though 2nd place goes to those raised in East South Central and who moved to NE, those raised in ESC also occupy 4 of the bottom 10 spots.

Why does growing up in MTN appear to boost your IQ? Probably because the climate is less favorable to the spread of pathogens by vectors that are migratory. And that, again, is probably due to less environmental heterogeneity in that area -- the Rockies are cold, dry, and very high in elevation, all tied to greater environmental stability. That's surely one reason why Colorado in particular performs so well, and its state government should publicize the hell out of Inductivist's findings to draw in wealthy parents who want the best environment for their kids. "Baby Einstein" pre-schools won't accomplish squat, but being raised in the salubrious climate of the Rockies sure will. Even the hot areas in the southern part of MTN, which are less impressive than the northern areas, are not humid or sub-tropical but desert, which is characterized by little environmental change over time or across space.

You might think that the lower population density is also a factor, and that could be, but people raised in regions with high density make a good showing in Inductivist's ranking. Population density is more critical in influencing acute, contagious diseases like the flu or perhaps rarer and wilder stuff like schizophrenia. But it could be that adult IQ is more influenced by the presence of chronic infections that continually disturb the development process. As before, knowledge of which pathogens and which vectors are the culprit is not necessary to believe this idea: just knowing that the local ecology in region X favors such things far more so than in region Y is enough to suspect that diminished IQ in region X is at least partly due to infection.

Moving on to larger concerns, one puzzle that I admitted in the original post was South Asian civilization -- isn't that one of the nastiest places to be climate-wise? I should've investigated further, because the answer is "yes and no." The climates in the Subcontinent vary a lot more than I thought, as you can see in this climate map of India and this climate map of the world. But does climate correlate with degree of civilization in South Asia? Beats me, since I couldn't say which areas over the long-haul show more development than which others. However, I have catalogued below a list of the climates for the capitals of South Asian civilizations beginning in the Neolithic. I used the chronology of Wikipedia's History of India article for convenience, and looked up the capitals there as well.

I'll leave it up to the more historically informed to say whether the hypothesis is supported or not My rough impression is that the North has shown greater development over the past several thousand years, even though the civilizations of the South and Bengal have been no slouches, but that may be wrong in general or perhaps correct broadly but wrong in finer detail. One interesting exception to the rule of Southern climates being more tropical, though, is that of Bangalore -- the "Silicon Valley of India" -- which enjoys a semi-arid climate, lies higher above sea level than Madrid (920 m vs. 667 m), and is known as a "Garden City."

And yes, I know that the current climates where the earliest civilizations flourished might not be identical to what they were at the time, but Iran and the modern countries occupying the Fertile Crescent also have mostly arid or semi-arid climates nowadays. The point is that they didn't consist of tropical wet & dry climates like you find in Sub-Saharan Africa or the Amazonian rainforests.

Civilization (:capital) -- climate

Mehrgarh -- arid

Indus Valley -- arid, semi-arid

Mahajanapadas -- arid, semi-arid, humid sub-trop

Magadha: Rajgir -- humid sub-trop

Maurya: Patna -- humid sub-trop

Satavahana: Pune, Paithan, Amaravati -- humid sub-trop

Kushan: Charikar -- highland, semi-arid; Taxila -- semi-arid; Mathura -- semi-arid

Gupta: Ujjain -- semi-arid; Patna -- humid sub-trop

Pala: Varendra / Rajshahi area -- humid sub-trop; also trop wet & dry

Chola: Tiruchirappalli -- semi-arid, trop wet & dry; Poomphuhar -- trop wet & dry; Gangaikonda Cholapuram -- trop wet & dry

Delhi Sultanate -- semi-arid

Deccan Sultanates -- semi-arid, trop wet & dry

Hoysala: Belur, Halebidu -- trop wet & dry

Kakatiya: Warangal -- trop wet & dry

Vijayanagara -- semi-arid

Mughal: Agra, Delhi -- semi-arid

Sikh Confederacy -- semi-arid, humid sub-trop

Maratha: Pune -- trop wet & dry

Post-Independence: New Delhi -- semi-arid; Islamabad -- semi-arid; Dhaka -- humid sub-trop, trop wet & dry

NB: I left out the period of colonial India for a few reasons that you might object to. First, Europeans certainly cope differently with non-European climates than do the locals, and I want to see whether climate affects degree of civilization even for those who are most adapted to life there. And second, it's my understanding that Europeans were more concerned with establishing superior trading posts and practicing mercantilism than they were with encourgaging civilization per se in South Asia.

Labels: civilization, climate, culture, IQ, pathogens

I just got an email that The Elf has decided to take aim at Cosma Shalizi's posts dismissing g & the heritability of IQ. Now, Cosma is an acquaintance of mine and we share some common interests, but here I hope the Elf and her kindred give him hell! Any GNXP readers with knowledge and spare time cycles should left the Elvenkind a helping hand.

Related: Tyler Cowen & Arnold Kling on IQ. And Michael Stansty too.

Labels: IQ

We all know that homo economicus fails as a complete description of human behavior, as the new field of behavioral economics makes abundantly clear. So while the homo economicus model does a good job explaining things like the interaction of supply and demand, the random walk nature of stock prices, and photo #16, it misses quite a lot of important facts about human behavior. By now, there's a rich literature on this, and any book you can find on the subject by Bowles, Camerer, or Thaler would give a good overview.

But of course, both h. economicus and h. behavioralis are ideal types--and so the question arises: Are some people more behavioral than others? Are some people more economistic that others? And is there any simple way to predict who will fit into which part of the spectrum?

Economists have started working on this question over the last few years, and right now I'll just stick to one small issue: Patience. The behavioralists have done a good job proving that people are generally much less patient than economic models predict. And recent work seems to show that smarter people are quite a bit more patient, a fact that may have important social implications.

In a recent study, Benjamin and Shapiro found that among Harvard undergrads, "A one-standard-deviation increase in mathematical performance raises the propensity to be patient by 18 percentage points, relative to a base of 28%." So if math scores rise by two standard deviations, patience more than doubles. Their summary:

In two laboratory studies [with Harvard students and Chilean high school students], we show directly that cognitive ability is associated with more standard time and risk preferences.

And what does "standard" mean to Benjamin and Shapiro? More like h. economicus.

Shane Fredrick of MIT showed much the same in this quite readable paper. He has a nice review of the earlier literature and in his own experiments found that "[t]hose who scored higher on the [cognitive reflection test] were generally more 'patient.'"

Both of those papers involve experiments with students playing for small sums of cash. This paper, published in what is arguably the top journal in economics, showed that when people were making decisions involving thousands of dollars, people with higher AFQT scores were much more patient.

The military drawdown program of the early 1990s provides an opportunity to obtain estimates of personal discount rates based on large numbers of people making real choices involving large sums. The program offered over 65,000 separatees the choice between an annuity and a lump-sum payment. Despite break-even discount rates exceeding 17 percent, most of the separatees selected the lump sum--saving taxpayers $1.7 billion in separation costs. Estimates of discount rates range from 0 to over 30 percent and vary with education, age, race, sex, number of dependents, ability test score, and the size of payment.

And when officers were broken down by careers, who were the most patient?

Engineers.

Labels: Economics, IQ

Tyler Cowen quotes from a new study testing the relationship between grades and delayed sexual activity.

Last December I passed a paper along to Razib showing that high-school age adolescents with higher IQs and extremely low IQs were less likely to have had first intercourse than those with average to below average intelligence. (i.e. for males with IQs under 70, 63.3% were still virgins, for those with IQs between 70-90 only 50.2% were virgin, 58.6% were virgins with IQs between 90-110, and 70.3% with IQs over 110 were virgins)

In fact, a more detailed study from 2000 is devoted strictly to this topic, and finds the same thing: Smart Teens Don't Have Sex (or Kiss Much Either).


The team looked at 1000s of representative teens grades 7-12 in the National Longitudinal Study of Adolescent Health and The Biosocial Factors in Adolescent Development datasets, both of which include an IQ test, and include detailed sexual experience questions ranging from hand-holding to intercourse. As with the other study there was a curvilinear relationship: students with IQs above 100 and below 70 were significantly less likely to have had intercourse than those in between. Also like the other study, they found teens with IQs ranging from 75 to 90 had the lowest probability of virginity (the authors note this is also the same IQ range where propensity towards crime peaks).



Depending on the specific age and gender, an adolescent with an IQ of 100 was 1.5 to 5 times more likely to have had intercourse than a teen with a score of 120 or 130. Each additional point of IQ increased the odds of virginity by 2.7% for males and 1.7% for females. But higher IQ had a similar relationship across the entire range of romantic/sexual interactions, decreasing the odds that teens had ever kissed or even held hands with a member of the opposite sex at each age.

While these authors leave off at grade 12th, it would seem plausible to expect that this relationship extends beyond high school. To explore this, plenty of interesting facts come from a 2001 campus sex survey by the joint MIT/Wellesley college magazine Counterpoint (PDF). Looking within and between colleges, IQ appears to delay sexual activity on into young adulthood.

By the age of 19, 80% of US males and 75% of women have lost their virginity, and 87% of college students have had sex. But this number appears to be much lower at elite (i.e. more intelligent) colleges. According to the article, only 56% of Princeton undergraduates have had intercourse. At Harvard 59% of the undergraduates are non-virgins, and at MIT, only a slight majority, 51%, have had intercourse. Further, only 65% of MIT graduate students have had sex.

The student surveys at MIT and Wellesley also compared virginity by academic major. The chart for Wellesley displayed below shows that 0% of studio art majors were virgins, but 72% of biology majors were virgins, and 83% of biochem and math majors were virgins! Similarly, at MIT 20% of 'humanities' majors were virgins, but 73% of biology majors. (Apparently those most likely to read Darwin are also the least Darwinian!)



Looking at this chart it would strongly appear that higher complexity majors contain more virgins than majors with lower cognitive demand. This paper provides me with GRE scores by academic discipline, and, in fact, the correlation between the percentage of virgins in each Wellesley major and the average 'Analytical' GRE score associated with the discipline is 0.60.

One reason we might guess that smarter people in high school, or in more challenging colleges or majors, delay their sexual debuts is because they are delaying gratification in expectation of future reward. Sexual behavior (or at least the investment needed to procure a partner or sustain one) may compete with time/resources required for other goals, and intelligent people may have more demanding goals. James Watson even hinted at this in a recent Esquire magazine piece:

If I had been married earlier in life, I wouldn't have seen the double helix. I would have been taking care of the kids on Saturday. On the other hand, I was lonely a lot of the time.

While sex may not be marriage, it may still require effort that intelligent people prefer to invest elsewhere. This would fit Aldus Huxley's alleged definition of an intellectual as a person who's found one thing that's more interesting than sex.

Another idea is that smarter people are more risk averse, and delaying these activities is a byproduct of enhanced concerns about unwanted pregnancy and disease. While not avoiding sexual behaviors, per se, they are just less likely to seek it out or consent to it for fear of the potential consequences.

Another idea is that smarter people are more religious or more ethically conservative, and are trying harder to wait for marriage to have sex.

Another idea, consistent with popular media portrayals of geeks and nerds (males at least), is that intelligent people actually want to have sex, but are simply less likely or unable to obtain willing partners because they are disproportionately viewed as unattractive or undesirable as partners.

Another idea is that intelligent people have lower general sex drives. This shouldn't be confused with the first theory, where their sex drives would be normal and they have greater self-restraint.

Some insightful digging by blogger Half Sigma into the General Social Survey, which also includes an abbreviated intelligence test, has turned up a number of associations that speak to these theories. The relationship between sexual activity and intelligence found across adolescence and young adulthood appears to continue on into adulthood proper.

Not only do intelligent people have a delayed onset of sexual behavior, Half Sigma found that they also have a lower number of premarital sex partners throughout adulthood (18-39). While this is consistent with the above theory that high IQ people are more religious and conservative, this is, of course, not true. Religiousness correlates with lower IQ, and as HS shows in the same post, intelligent people were also more likely to say that premarital sex was not immoral. (Leaving those who did think it was immoral to participate in the bulk of it!) Most of the other theories are still consistent with this finding though.

Perhaps more revealing, HS, also showed that intelligence correlates with less sex within marriage for the same age range. While still consistent with pregnancy fears and competing interests, lower sex drive seems like a better fit. In fact another revealing finding from the Counterpoint survey was that while 95% of US men and 70% of women masturbate, this number is only 68% of men and 20% of women at MIT!

Also the idea that more intelligent people are too busy for the opposite sex not just in 7th grade to college, but throughout adulthood and for their own spouse, seems unrealistic. In fact the GSS also shows (PDF) that smarter people spend more time socializing with their friends, indicating their hours aren't spent as uniquely isolated and narrowly channeled as the theory would require.

But lower sex drive and anxiety about sex's consequences can't be the whole story either. Half Sigma also showed that the smartest men in the GSS (approx. IQ >120) were also more likely to visit a prostitute. (Hardly indicative of cautiousness) This may suggest intelligent men are less able to find willing sex partners. Are smart men less attractive to women? Perhaps in some ways. For instance HS found that smart men were less likely to be athletic, and this paper shows, unathletic men and women have fewer sex partners. Athletic men, with more willing sexual partners are also less likely to visit a prostitute. Athletic activity gives men more masculine bodies, which are more attractive to women. A more masculine physique correlates with (PDF) an increased number of sex partners.

So intelligent people have lower libidos and less masculine physiques. What hormone is responsible for both sex drive and masculine builds? That's right: testosterone.

And two new papers suggest that testosterone may depress IQ. One team found that salivary testosterone levels were lower for preadolescent boys with IQs above 130 and below 70. (the same two groups most likely to be virgins in adolescence)

Another paper suggests that a gene responsible for androgen sensitivity and higher sperm counts may also create a tradeoff for intelligence.

Labels: IQ, sex, Testosterone

John Quiggin @ Crooked Timber has a post where he moots ideas re: IQ & height. If you're inclined to give David Kane a helping hand, swing on over! Just remember, the gang @ CT are much, much, smarter than you, so tread lightly....

Labels: height, IQ, Psychology

The NYT reports that a completely revised GRE has been deep sixed, not merely delayed (read the ETS press release here). The official story is that there is some insurmountable problem with providing access to all test-takers, an issue apparently too complicated for ETS to bother trying to explain it to us. You figure, since this was such a huge project that was suddenly halted, they'd want to clearly spell out why they dumped it -- unless that's the point. Although I'm no mind-reader, the true reason is pretty obvious: the made-over test was designed to narrow the male-female gap at the elite score level, but this diluted its g-loadedness such that it couldn't reliably distinguish between someone with, say, a 125 IQ and a 145+ IQ, which is what graduate departments who rely on super-smart students worry about. Rather than admit that this psychometric magic trick went awry and lopped off a few limbs of g-loadedness, they spun a yarn about access to the test. [1]

To put this in perspective, for those who took the SAT before spring 2005 -- which is everyone here, I assume -- the New SAT now includes a Writing test with both multiple choice grammar questions and a 25-minute persuasive essay. No admissions committee is paying serious attention to this silly addition, although high schoolers obsess over it. The real changes are that the Math test no longer includes the "quantitative comparison" questions (column A, B, equal, can't tell?), and the flavor of the questions is a bit more "book smarts"-based than before. Also, the Verbal test (now called Critical Reading) has zero analogies, fewer sentence completions, and much more passage-based reading. The gutted portions are those that are more highly g-loaded, for sure in the Verbal test, and most likely in the Math test as well. [2]

We now ask why ETS intentionally stripped the SAT of some of its g-loadedness? Certainly not because they discovered IQ had little value in predicting academic performance, or that some items tap g more directly than others -- so why re-invent the wheel? Since scores on various verbal tasks highly correlate, this change cannot have affected much the mean of any group of test-takers. But if getting a perfect score required scoring correctly on, say, 10 easy questions, 5 medium, and 5 difficult (across 3 sections), a greater number of above-average students can come within striking distance of a perfect score if the new requirement were 10 easy, 9 medium, and 1 hard. I don't know exactly how they screwed around with the numbers, but that's what they pay their psychometricians big bucks to do. Now, reducing the difficulty of attaining elite scores, without also raising mean scores (as with the 1994 recentering), can only have had the goal of reducing a gap that exists at the level of variance, not a gap between means. This, then, cannot be a racial gap but the male-female gap, since here the difference in means is probably 0-2 IQ points, although male variance is consistently greater.

Certainly this reduces the power of the SAT to detect very brainy people -- those with an IQ of 145 or 160 or whatever big number you want -- but I can easily imagine that both ETS and elite universities such as Harvard were willing to trade off a bit of g-loadedness in order to close the male-female gap at the elite level. Harvard students wouldn't look stupider, of course: their prestige is based on their mean SAT score compared to those of others. And they probably have other ways of figuring out who is very brainy vs. fairly smart. (As an aside, this also explains why lots more high-scoring applicants will be rejected by top schools, another paradox that is easily, even if only partially, resolved by clear thinking.) Moreover, attending Harvard isn't all about having a 145 IQ -- a non-trivial number of their graduates will join professions that don't require eigth-grade algebra or sophisticated analysis (say, political office). So that, too, may lessen their concern over the SAT becoming somewhat less g-loaded.

Not so with the GRE -- those who score at the elite level here are hardcore nerds who are planning to do serious intellectual work, and elite graduate departments pay attention mostly to the applicant's intellectual promise. MIT's math department probably doesn't care that an applicant scored 650 on the Math portion but showed singular potential for leadership roles. So, I imagine something similar to the SAT make-over happened, only this time the professors and/or ETS' psychometricians discovered that it would make a joke of a test used to detect the very brainy in search of elite graduate work.

To make this concrete, let's assume that, among applicants to graduate school in the arts and sciences (i.e., future scholars, not professionals), males enjoy only a 0.1 SD advantage in mean IQ (or 1.5 IQ points), as well as a 0.05 SD advantage in their standard deviation. Then a test that is reliable up to 3 SD above the female mean will have 30% of those above this threshold being female. (For comparison with the real world, grad students at CalTech are 30% female.) Almost 10 percentage points can be gained by dumbing the test down so that it's only reliable up to about 2 SD, in which case 39% at the top will be female. Dumbing it down further so that it can only detect those 1 SD above the female mean just adds about 5 further percentage points; females will make up 45%. My guess is that they weren't foolish enough to toy around with a GRE that only tested up to an IQ of 115, but that they took a risk on some version that tested up to about an IQ of 130. Though that's just about enough to get you into MENSA, the real hullabaloo over sex disparities has raged within the halls of the uber-elite: Harvard (Larry Summers), MIT (Nancy Hopkins), Stanford (Ben Barres), and so on. At such an elite level, an applicant with an IQ of 130 would be like a 6'3 guy trying out for the NBA (whose mean height is 6'7). Although the NBA doesn't automatically weed out those 6'3 and under, surely the recruiters would protest to the manufacturers if their new-fangled measuring sticks only measured up to 6'3!

Pursuing this hunch, I picked up my Kaplan GRE self-study book and found out that they knew at least roughly what the new GRE was going to look like. Here were the proposed new question types for Verbal and Math:

Verbal
Reading Comprehension (4 types)
Sentence Completion (2 types)

Math
Word Problems (4 types)
Data Interpretation (2 types)
Quantitative Comparison (1 type, as before)

Notice the huge change in the Verbal test, which parallels the change in the SAT Verbal test: analogies are gone, and most of the test is reading comprehension. As for Math, they did keep the Quant Comps, but most of the new question types thereof sound too touchy-feely to be of good use: Word Problems include old-fashioned ones, plus "Free Response," "All That Apply," and "Conditional Table" (Kaplan admits they didn't know the exact names -- maybe the last was a contingency table type?). "Free Response" sounds like it would be more g-loaded since you can't rely on answer choices, but it definitely isn't, at least not if this type was to resemble its counterpart on the SAT. Here, you grid in your own answer, but only non-negative rational numbers can be gridded, precluding the use of any questions whose answer had a root or exponent or absolute value, whose trick hinged on the properties of positives vs negatives vs 0, whose answer was an equation or inequality, and most importantly whose point was abstract symbol manipulation (such as "solve for V in terms of p, q, and r"). Since females are better than males at calculation, and worse than males on more abstract math problems, "Free Response" is an easy way to obscure the male advantage at "thinking" math.

Not knowing much about what the other two new types of Word Problems are, I think it's still safe to say they were just as vacuous. In fact, the Data Interpretation problems were to come in 2 types: the old-fashioned one, and a new one called -- don't laugh -- "Sentence Completion"! For christ's sake, why not just turn some of the harder ones into Writing problems in disguise, where the test-taker corrects the grammar of a word problem rather than actually solve it! This psychometric flimflam is ultimately what all would-be gap-reducers must reduce themselves to, at least when the concern is the sex gap at uber-elite levels where those who matter will brook no nonsense over the basic tests being dumbed down.

[1] Since I'm pretty tired by now of writing about the "women in science" topic, for background info I'll just link to a very lengthy post of mine on point, plus Steven Pinker's debate with Elizabeth Spelke.

[2] See p.2 of the full PDF linked to in this post from the GNXP archives. It contains a graphic showing the g-loadedness of various cognitive tasks. Analogies are the most highly g-loaded verbal tasks, reading comprehension one of the least so (though still enough to validate its use on tests).

Labels: IQ, psychometric smoke and mirrors, sex differences

Sleep Disorders Can Impair Children's IQs As Much As Lead Exposure

UVa researchers have been studying sleep disturbances in children with enlarged tonsils and adenoids for the past seven years. In a recent study, they discovered that youngsters who snore nightly scored significantly lower on vocabulary tests than those who snore less often.
...
According to Dr. Suratt, the vocabulary differences associated with nightly snoring are equivalent to the IQ dissimilarities attributed to lead exposure. "Studies show that, even at nontoxic levels, lead exposure can reduce a child's IQ by more than seven points," he notes.
...
In a series of studies involving six to twelve-year-olds, researchers have been piecing together a list of risk indicators. So far, snoring frequency combined with sleep lab results have proven to be the most reliable predictors of intellectual impairment and behavioral problems. Sleep duration and race appear to be important risk factors, too.


This study only shows correlation but when combined with research showing the importance of sleep for consolidating memories the story becomes interesting. Perhaps treatments that improve sleep quality will increase IQ?

Labels: IQ, Sleep

lwka's excellent post below mentions (among other things) the low reported IQ in African countries.

When this came up on a previous occasion the question was raised whether mean IQ's of 70 or even lower for Africans were compatible with a 'black' mean IQ of 85 in the United States, after taking account of the mixed African and European ancestry of American blacks.

At that time I did a few sums and started writing a post, but never quite finished it. But I have dusted it off and posted it below the fold, as it still seems relevant.


First, some assumptions:

- for the sake of this discussion, I assume that all group differences are wholly genetic in origin. Of course, I don't believe this, and I'm not sure that anyone does.

- I assume that the observed mean IQ of white Americans, on current (2000-ish) norms, is 100, and that of 'black' Americans is 85

- I started by assuming that, on average, 'black' Americans have 20% white ancestry. However, having done all the calculations on this basis and written up the results, I found that a figure of 25% is also sometimes used (e.g. by Jensen). This seems rather high, (see the figures in Sandra Scarr's Race, Social Class and Individual Differences in IQ), but I have repeated the calculations on this basis as an alternative. Rather than present two sets of workings, I have just inserted the key alternative results in square brackets. Whether on the 20% or 25% basis, I assume that the white ancestry of 'blacks' is genetically representative of the white American population.

Needless to say, all of these assumptions could be discussed at length.

With these assumptions, if all genetic effects are strictly additive, with no dominance or epistasis, then the mean IQ of an unmixed 'black' population would be X, where .8X + .2(100) = 85, which gives the value X = 81.25 [or 80 on the alternative 25% basis]. This is the easy bit!

But it is unlikely that all the genes affecting IQ are purely additive. To consider the possible effects of dominance, let us assume that all genes affecting IQ have two alleles, H (High) and L (Low), with H dominant. To take the most extreme assumption for gene frequencies, maximising the effect of dominance in differentiating a 'pure' black population from a black-white mixture, let us assume that the white population is entirely homozygous for the dominant H, while the ancestral black population is entirely homozygous for the recessive L. The US mixed 'black' population would therefore have a gene frequency at each locus of 80% L and 20% H. In Hardy-Weinberg equilibrium this gives genotype frequencies of .64LL, .32HL, and .04HH. The phenotypic value of each locus in the US 'black' population would therefore be .64X + (.32 + .04)100 = 85, where X is the unknown phenotypic value of the 'pure' black population. This gives X = 76.56 [or 73.2 on the 25% basis].

This is not a realistic assumption for gene frequencies, since if it applied to all loci the 'pure' populations would be genetically uniform, which is obviously not the case. To consider a more plausible model for gene frequencies, suppose the frequency of H is 60% in the white population and 30% in a pure black population, so that the frequency of L is 40% in the white population and 70% in a pure black population (since the frequency of H + L must be 100% for each population.) For the US 'black' population the frequencies are therefore (.8 x 30%) + (.2 x 60%) = 36% for H, and 64% for L. The Hardy-Weinberg genotype frequencies for the white population are 36%HH, 48%HL, and 16%LL and for the US 'black' population (approx) 13%HH, 46%HL, and 41%LL. If we designate the phenotypic value of HH and HL as X (not to be confused with the previous X!) and of LL as Y, we get two equations as follows:

(.36 + .48)X + .16Y = 100
(.13 + .46)X + .41Y = 85

Solving these equations gives (approx) X = 109.6 and Y = 49.6 [or 110.4 and 45.4 on the 25% basis].

In a 'pure' black population with gene frequencies of 30% H and 70% L, and Hardy-Weinberg genotype frequencies, these results give a mean phenotypic value for the population of almost exactly 80 [78.5 on the 25% basis], as compared with 81.25 [80 on the 25% basis] if there is no dominance. It will be seen that in this model the effect of dominance in differentiating 'pure' from 'mixed' black population is not very great.

These are in principle the values for a single locus. In the absence of epistasis, the mean value for the genome as a whole is simply the mean value of all relevant loci.

Epistasis, by definition, means that the phenotypic value of the genome varies according to the particular combination of genes at different loci. Essentially the only limit on possible epistatic effects is the ingenuity of the model-maker. As a general rule, epistasis is less important than dominance, so my gut feeling is that epistasis, on any plausible model, is unlikely to make much difference to the conclusions above. If anyone disagrees, let them set out a plausible model in which it does make a difference. Note that if high white IQ is due to favourable epistatic gene combinations, these are very likely to be broken up in a 'black' population with only 20% or 25% white ancestry, so that in this respect the difference between a 'pure' black population and the US 'black' population would probably be small.

Departures from Hardy-Weinberg equilibrium would also be a complication. Assortative mating within the US 'black' community for traits deriving from white ancestry, such as skin colour or IQ (assuming that this is genetic), would tend to increase the proportion of homozygotes above the Hardy-Weinberg expected levels. This would reduce the overall phenotypic contribution of white ancestry, since the same number of dominant H genes would be distributed among fewer individuals than in Hardy-Weinberg equilibrium. In effect, one of the dominant genes is 'wasted' in a homozygote. On the other hand, first generation black-white hybrids would have a higher proportion of heterozygotes than the rest of the 'black' population. One prediction of a purely genetic model assuming dominance for high-IQ genes is that the IQ of first-generation mixed-race individuals would be closer to the white mean IQ. But this would presumably affect only a small proportion of the 'black' population as a whole.

I haven't bothered calculating the effects on the assumption that the genes for low IQ are dominant. Obviously in that case the 'mixed' black population would be closer to the 'pure' black population.

The general conclusion is, I think, that on hereditarian assumptions about the nature of the black-white IQ difference in the US, the genetic IQ of a 'pure' black population cannot be much below 75 and is more likely around 80. (Note that this is by present-day norms. Due to the Flynn Effect, a present-day score of 80 would have corresponded to about 100 when IQ tests were first established.) This is higher than the mean IQ (often below 70) sometimes reported for black African countries from which the black ancestry of 'black' Americans is derived. Of course, one could in principle argue that the Africans who were taken to the US were above average in genetic IQ (relative to other Africans), but this is hardly likely. Alternatively, one could argue that 'black' Americans have improved their genetic IQ, and/or that African genetic IQ has deteriorated, in the 250 years or so since the slaves arrived in America. Neither hypothesis seems plausible.

It would therefore be difficult to consistently maintain a purely hereditarian view of both the black-white difference in the US and the low measured IQ of black Africans. I am not sure that anyone has actually take this position, but it may still be worth pointing out the difficulties.

Labels: IQ

In IQ and the Wealth of Nations (2002; IQatWoN) and IQ and Global Inequality (2006; IQGI), Richard Lynn and Tatu Vanhanen (L&V) present measurements and estimates of average national IQ (national IQ). In IQatWoN, L&V argue that national IQ predicts per-capita GDP (sup Fig 1). In IQGI, L&V argue that national IQ predicts quality of life measures (sup Fig 2). A common criticism of both works is to question the validity of national IQ. This criticism is motivated in part by the very low scores reported for countries in sub-Saharan African. A look at the distribution of national IQ is instructive (Fig 1).

Figure 1. The distribution of national IQ values (192 countries from IQGI).


L&V address the issue of validity by comparison of national IQ values with international test scores in math and science such as TIMSS and PISA. IQGI presents data from 10 different tests, with different scoring scales, in the form of 3 tables. To get a better grasp on the question of the validity of national IQ, I reanalyzed the test score data from IQGI. For better comparison, I renormalized each set of test scores relative to the maximum test score for each assessment. This is an imperfect but sufficient technique. An unweighted average of the available test score data was used to calculate a composite national test score for the set of 62 countries for which at least 1 test score was available (Fig 2).

Figure 2. The association between national test scores and national IQ for 62 nations.


National test scores are available for a limited range of national IQ scores, with few test scores available for countries with national IQs below the mid 80s. I interpret this to mean that for countries with national IQs below ~85, the test score data is insufficient to inform the question of validity. However, for the available scores (i.e., mostly above ~85), the relationship between national IQ and national test scores is very strong (see Sup Table 1).


The validity of sub-80 national IQs is addressed in part by the finding that IQ correlates with GDP and QHC (Sup Figs 1,2) throughout the observed range of IQ.

Update: Although there are only four values, the sub-80 national IQs are outliers, all with positive residuals. While this is hardly informative, it trends in the direction of casting doubt on the validity of sub-80 national IQ values.

Supplemental Figure 1. National IQ correlates with GDP per-capita (192 countries from IQGI).


Supplemental Figure 2. National IQ correlates with a L&V's quality-of-life index (QHC; 192 countries from IQGI).


Supplemental Table 1. Correlation matrix for national IQ (IQ), national test score (Test), L&V's quality of life index (QHC) and log per-capita GDP (logGPD) for 62 countries.

r	QHC	logGDP	IQ	Test
QHC	1	0.898936	0.7933265	0.7803476
logGDP	0.898936	1	0.760138	0.7565582
IQ	0.7933265	0.760138	1	0.9008035
Test	0.7803476	0.7565582	0.9008035	1

Related papers:
* Earl Hunt and Werner Wittmann, National intelligence and national prosperity, Intelligence, In Press --examines PISA scores
* Richard Lynn and Jaan Mikk, National differences in intelligence and educational attainment, Intelligence, Volume 35, Issue 2, March-April 2007, Pages 115-121. --examines TIMSS scores

Labels: general intelligence, IQ

Jensen (1998) makes a point that is worth repeating:

The pernicious notion that IQ discriminates mainly along racial lines, however, is utterly false.

Jensen presents what should be a predictable pattern for a highly heritable trait:

Source	% of Variance		Average IQ Difference
Between races (within social classes)	14	30	12
Between social classes (within races)	8		6
Interaction of race and social class	8
Between families (within race and social class)	26	65	9
Within families (siblings)	39		11
Measurement error	5		4
Total	100		17

This can be demonstrated most clearly in terms of a statistical method known as the analysis of variance. Table 11.1 shows this kind of analysis for IQ data obtained from equal-sized random samples of black and white children in California schools. Their parents' social class (based on education and occupation) was rated on a ten-point scale. In the first column in Table 11.1 the total variance of the entire data set is of course 100 percent and the percentage of total variance attributable to each of the sources6 is then listed in the first column. We see that only 30 percent of the total variance is associated with differences between race and social class, whereas 65 percent of the true-score variance is completely unrelated to IQ differences between the races and social classes, and exists entirely within each racial and social class group. The single largest source of IQ variance in the whole population exists within families, that is, between full siblings reared together in the same family. The second largest source of variance exists between families of the same race and the same social class. The last column of Table 11.1 shows what happens when each of the variances in the first column is transformed into the average IQ difference among members of the given classification. For example, the average difference between blacks and whites of the same social class is 12 IQ points. The average difference between full siblings (reared together) is 11 IQ points. Measurement error (i.e., the average difference between the same person tested on two occasions) is 4 IQ points. (By comparison, the average difference between persons picked at random from the total population is 17 IQ points.) Persons of different social class but of the same race differ, on average, only 6 points, more or less, depending on how far apart they are on the scale of socioeconomic status (SES). What is termed the interaction of race and social class (8 percent of the variance) results from the unequal IQ differences between blacks and whites across the Spectrum of SES, as shown in Figure 11.2. This interaction is a general finding in other studies as well. Typically, IQ in the black population is not as differentiated by SES as in the white population, and the size of the mean W-B difference increases with the level of SES.

Labels: general intelligence, IQ, race

Wherever the abilities involved are sufficiently distinct--and that is in the great majority of cases--our tetrad equation is satisfied with surprising exactitude, so that here each ability must be divisible into g and s. The letter g becomes, in this manner, a name for the factor--whatever it may be--that is common to mental tests of such a description. This is the very definition of g. (Spearman, 2005, p. 161)

General intelligence (g) has been one of the most, if not the most, aggressively studied constructs in psychology. Type the search string "general intelligence" in PsycInfo and you will return over 2000 entries, and a similar search in Pubmed pulls up over 400. If you broaden the term to just "intelligence", the respective number of entries are 65405 and 37166. While not all of the results focus on g , (e.g., AI, "social intelligence"), a large portion of them do, and the prospect of meandering your way through can be intimidating. Fortunately, the overall literature is consistent and, at least for me, highly engaging.

The study of g can be bifurcated into two distinct areas: vertical and horizontal g . Vertical g is the domain that studies g's biological relationships. It is the area that is going to eventually assimilate enough data and literature to elucidate, unquestionably, the causal mechanisms of g . From this field of study, we know that g is correlated with a variety of neural mechanisms, such at glucose metabolism (Haier, 2003), cortical development (Shaw et al., 2006), and biochemical activity (Jung et al., 2005). We know that g is highly heritable, both when measured psychometrically (Plomin & Spinath, 2002) or chronometrically (Beaujean, 2005). We know that g decreases with inbreeding (Jensen, 1983) and increases with hybrid vigor (Nagoshi & Johnson, 1986). As genome scanning becomingmore popular, we are now even beginning to see some specific genes that are implicated g.

As interesting as vertical g is, however, this entry is going to instead focus in the horizontal aspects of g . That is, how does g play out into "everyday life." Specifically, we will look three different, although related, areas: education, occupation, and general life outcomes. The reasons for doing so are twofold: (a) the more the science of horizontal g is positively promulgated, then, perhaps, the more likely people are to support the needed research into vertical g and (b) even though this area of research has been around for over a century (e.g., Galton, 1869), there are still new, important findings.

Before delving into horizontal g, however, it would behoove us to delineate a mechanism by which g could influence education, occupation, and general life outcomes.For our purposes, that mechanism is information processing. Generally defined, information processing is the pathway and mechanisms by which stimuli are perceived, attended to, retrieved, and/or used to solve problems and/or cope with exigencies in the environment (Jensen, 1998a). The cognitive psychology literature is chalked full of the nuances of the various information-processing theorists, the specifics are which cannot be delineated here (an easy-to-read intro: Ormrod, 2004). Yet, within all these theories lies the idea that people respond to stimuli in a way that involves many mechanisms (e.g., sensory register, primary memory)and a variety of neurological regions (e.g., hippocampus, amygdala, mammillary bodies). The consequence? There is ample room for individual differences in the speed and efficiency in which information is processed.

From another perspective (e.g., Kline, 1998), information is processed in irreducibly small pieces (often called bits) and the time it takes to process those bits is the BIP, the Basic period of Information Processing. Now, the time it takes Johnny to process the fact that the only integer between 2 and 4 is 3 is going to be different than the time it takes Jane. Multiply those differences by the number of people processing the fact, and voila! individual differences.

Educational Outcomes

This is probably the area most replete with data and, unsurprisingly, the g-educational achievement relationship is strong. In fact, although it differs by grade level (with it decreasing as grade level increases), most of the non-random variance in scholastic performance is accounted for by g (Thorndike, 1984). Jensen (1989, 1998b) writes that this is so due to the fact that "school learning" is, itself, quite g -loaded. Of course, there are those who write that g is just a product of education (e.g., Ceci, 1991; for a review of others, see Gottfredson, 1986), or, perhaps more egregious, that g and educational achievement are just products of the tests designed to measure them (for review and rebuttal, see Jensen, 1984). But these arguments quickly dissipate when looking at the evidence.

For example, in the latest issue of Intelligence, there were two longitudinal studies (Deary, Strand, Smith, & Fernandes, 2007; Watkins, Lei, & Canivez, 2007) that showed a strong IQ --> Educational Achievement relationship (approx. 70 from Deary), but reverse (i.e., EA --> IQ) was not there (from the Watkins study). Further evidence comes from the two major "We can improve you Education by improving your IQ" projects: Head Start and the Abecedarian Study. With regard to the former, Head Start just does not produce long-term IQ gains and, hence, does not produce long-term academic gains (Caruso, Taylor, & Detterman, 1982; Holden, 1990; Kreisman, 2003). With regard to the latter, while there has been acrimonious debate, the overall conclusion is that, like Head Start, the initial IQ gains do not last, giving even more evidence that educational achievement cannot be raised independently of g (Spitz, 1986, 1992, 1993b, 1993a).

Yet another line for arguing against the prominence of g in education is the idea that there are other traits that are just as necessary for academic success, such as motivation, personality, etc. To risk sounding like to broken record, the data shows that these traits are not nearly as potent predictors as g in predicting academic outcomes. For example, Gagne and St. Pere (2002) gives us reason to believe that motivation might just be an impotent variable in predicting academic achievement. Likewise, Laidra, Pullmann, and Allik (2007) have shown that while personality factors contribute some to the variance in educational achievement, they are dwarfed in comparison to the contribution of g.

Occupational Outcomes


There are many theories as to how g and occupational outcomes relate (see Gottfredson, 1986), but the one that is most supported by data is best explicated by Frank Schmidt and John Hunter

[g] predicts both the occupational level attained by individual and their performance within their chosen occupation. [g] correlates above .50 with later occupational level, performance in job training programs, and performance on the job. Relationships this large are rare in psychological literature and are considered "large" . . . weighted combinations of specific aptitudes (e.g., verbal, spatial, or quantitative aptitude) tailored to individual jobs do not predict job performance better than [g] measures alone, thus disconfirming the specific aptitude theory. It has been proposed that job experience is a better predictor of job performance than [g], but the research findings . . . support the opposite conclusion. . . . Nearly 100 years ago Spearman (1904) proposed that the construct of [g] is central to human affairs. The research . . . supports his proposal in the world of work, an area of life critical to individuals, organizations, and the economy as a whole.(Schmidt & Hunter, 2004, p.171; cf.Schmidt & Hunter, 1998)

One could argue that, given the high g -education relationship, that the g-occupation relationship is just a natural outgrowth.That is, once education is controlled, the g-occupation relationship significantly shrinks. But to make that argument, one would have to have a Sternberg-like approach to intelligence (Sternberg & Wagner, 1993). That is, that the cognitive skills needed for a successful education are somehow vastly different than those needed for everyday life. The data, however, indicate that the same generative process that tends to makes one successful in the educational arena is also the mechanism that tends to make one successful in the occupational arena: g (Kuncel, Hezlett, & Ones, 2004). This is not to say that other things are not important in occupational or educational outcomes; but, as with education, they are not nearly as potent predictors (Gottfredson, 2002).

Life Outcomes

Over the last decade or so, an area that has become of more interest to the intelligence community is the influence of g on general life outcomes. That is, beyond educational and occupational outcomes, does g contribute to life success? The answer here, too, seems to be a resounding yes.

IQ scores [a proxy for g] predict a wider range of important social outcomes and they correlate with more personal attributes than perhaps any other psychological trait. The ubiquity and often-considerable size of g's correlations across life's various domains suggest g truly is important in negotiating the corridors of daily life. (Gottfredson, 2003, p. 326)

But how does g relate to general life outcomes? Believe it or not, it appears that the same information-processing mechanisms that are so potent for educational and occupational outcomes also play a role in day-to-day life (Gottfredson & Deary, 2004). Gottfredson (2003, 2004b) elaborates this mechanism as follows: Life is is made up of many tasks with a wide array of complexity (Gordon, 1997). In the US and most Western nations, society is "free enough" for competence (read: g ) to make a substantial difference in who succeeds in life. As those who have "higher g" are more able to tackle the day-to-day activities of life successfully with less exerted effort, they are able to progress in life with fewer impediments (e.g., untreated illness, accidents; Gottfredson, 2004a), thus allowing them to (a) have more resources to successfully compete and (b) be able to use their resources more efficiently. This then not only allows for a higher probability of achieving satisfying life outcomes (e.g., adequate income, occupational autonomy), but also allows for a lower probability of being involved with unsatisfying life outcomes (e.g., having children without means to support them, crime/delinquency) (cf. Ellis & Walsh, 2003; Herrnstein & Murray, 1996)

Conclusion

Given the ubiquity of g in fostering success in many life outcomes from education achievement to occupational success, from health outcomes to criminal recidivism, social science in general and psychological science in particular would be remiss to "pretend it doesn't matter" (Gottfredson, 2000). Rather, if these fields want to strengthen their scientific integrity and acumen, they should do exact opposite. That is, bring the large, cumulative database on g and its influence on life outcomes to the forefront of a wide array of research agendas so that this corpus of data can serve as the strong underlying foundation of a generation of new investigations on g's life implications. While this line of investigation may never get to the underlying (vertical) mechanisms by which g operates, it can help foster the acceptance of doing such research and pave the way for its societal implications, whatever they may be.

References

Beaujean, A. A. (2005). Heritability of mental processing speed as measured by mental chronometric tasks: A review and meta-analysis. Intelligence, 33, 187-201.

Caruso, D. R., Taylor, J. J., & Detterman, D. K. (1982). Intelligence research and intelligent policy. In D. K. Detterman & R. J. Sternberg (Eds.), How and how much can intelligence be increased? (pp. 45-65). Norwood, NJ: Ablex.

Ceci, S. J. (1991). How much does schooling influence general intelligence and its cognitive components? A reassessment of the evidence. Developmental Psychology, 27, 703-722.

Deary, I. J., Strand, S., Smith, P., & Fernandes, C. (2007). Intelligence and educational achievement. Intelligence, 35, 13-21.

Ellis, L., & Walsh, A. (2003). Crime, deliquency, and intelligence: A review of the worldwide literature. In H. Nyborg (Ed.), The scientific study of general intelligence: Tribute to Arthur R. Jensen (pp. 343-365). New York: Pergamon.

Gagne, F., & St. Pere, F. (2002). When IQ is controlled, does motivation still predict achievement? Intelligence, 30, 71-100.

Galton, F. (1869). Hereditary genius: An inquiry into its laws and consequences. London: MacMillan.

Gordon, R. A. (1997). Everyday Life as an Intelligence Test: Effects of Intelligence
and Intelligence Context. Intelligence, 24, 203-320.

Gottfredson, L. S. (1986). Societal consequences ofthe g factor in employment. Journal of vocational behavior, 29, 379-410.

Gottfredson, L. S. (2000). Pretending that intelligence doesn't matter. Cerebrum, 2, 75-96.

Gottfredson, L. S. (2002). g: Highly general and highly practical. In R. J. Sternberg & E. L. Grigorenko (Eds.), The general factor of intelligence: How general is it? (pp. 331-380). Mahwah, NJ: Erlbaum.

Gottfredson, L. S. (2003). g, jobs, and life. In H. Nyborg (Ed.), The scientific study of general intelligence: Tribute to Arthur R. Jensen (pp. 293-342). New York: Pergamon.

Gottfredson, L. S. (2004a). Intelligence: Is it the epidemiologists' elusive "fundamental cause" of social class inequalities in health? Journal of Personality and Social Psychology, 86, 174-199.

Gottfredson, L. S. (2004b). Life, death, and intelligence. Journal of Cognitive Education and Psychology, 4, 23-46.

Gottfredson, L. S., & Deary, I. J. (2004). Intelligence predicts health and longevity, but why? Current Directions in Psychological Science, 13, 1-4.

Haier, R. J. (2003). Brain imaging studies of intelligence: Individual differences
and neurobiology. In R. J. Sternberg, J. Lautrey, & T. I. Lubart (Eds.), Models of intelligence: International perspectives (pp. 185-193). Washington, DC: American Psychological Association.

Herrnstein, R. J., & Murray, C. (1996). Bell curve: Intelligence and class structure in American life. New York: Free Press.

Holden, C. (1990, March 23). Head Start enters adulthood. Science, 247, 1402.

Jensen, A. R. (1983). The effects of inbreeding on mental ability factors. Personality and Individual Differences, 4, 71-87.

Jensen, A. R. (1984). Test validity: g versus the specificity doctrine. Journal of Social and Biological Structures, 7, 93-118.

Jensen, A. R. (1989). The relationship between learning and intelligence. Learning
and Individual Differences, 1, 37-62.

Jensen, A. R. (1998a). The g factor and the design of education. In R. J. Sternberg & W. M. Williams (Eds.), Intelligence, instruction, and assessment: Theory into practice (pp. 111-131). Mahwah, NJ: Lawrence Erlbaum.

Jensen, A. R.(1998b). The g factor: The science of mental ability. Westport, CN: Praeger.

Jung, R. E., Haier, R. J., Yeo, R. A., Rowland, L. M., Petropoulos, H., Levine, A. S., et al. (2005). Sex differences in N-acetylaspartate correlates of general
intelligence: An 1H-MRS study of normal human brain. Neuroimage, 1, 965-972.

Kline, P. (1998). The new psychometrics: Science, psychology and measurement. London: Routledge.

Kreisman, M. B. (2003). Evaluating academic outcomes of Head Start: An application of general growthmixture modeling. Early Childhood Research Quarterly, 18, 238-254.

Kuncel, N. R., Hezlett, S. A., & Ones, D. S. (2004). Academic performance, career
potential, creativity, and job performance: Can one construct predict them all? Journal of Personality and Social Psychology, 86, 148-161.

Laidra, K., Pullmann, H., & Allik, J. (2007). Personality and intelligence as predictors of academic achievement: A cross-sectional study from elementary to secondary school. Personality and Individual Differences, 42, 441-451.

Nagoshi, C. T., & Johnson, R. C. (1986). The ubiquity of g. Personality and Individual Differences, 7, 201-207.

Ormrod, J. E. (2004). Human learning (4th ed.). Upper Saddle River, NJ: Pearson.

Plomin, R., & Spinath, F. M. (2002). Genetics and general cognitive ability (g). Trends in Cognitive Science, 6, 169-176.

Schmidt, F. L., & Hunter, J. (1998). The validity and utility of selection methods in personnel psychology practical and theoretical implications of 85 years of research findings. Psychological Bulletin, 124, 262-274.

Schmidt, F. L., & Hunter, J. (2004). General mental ability in the world of work: Occupational attainment and job performance. Journal of Personality and Social Psychology, 86, 162-173.

Shaw, P., Greenstein, D., Lerch, J., Clasen, L., Lenroot, R., Gogtay, N., et al. (2006, Mar 30). Intellectual ability and cortical development in children and adolescents. Nature, 440, 676-679.

Spearman, C. E.(1904). "General intelligence": Objectively defined and measured.
American Journal of Psychology, 15, 201-292.

Spearman, C. E.(2005). The abilities of man: Their nature and measurement. New York: Blackburn Press (Original work published 1927).

Spitz, H. H. (1986). The raising of intelligence: A selected history of attempts to raise retarded intelligence. Hillsdale, NJ: Lawrence Erlbaum Associates.

Spitz, H. H.(1992). Does the Carolina Abecedarian Early Intervention Project prevent sociocultural mental retardation? Intelligence, 16, 225-237.

Spitz, H. H. (1993a). Spitzs reply to Ramey's response to Spitz's first reply to Ramey's first response to Spitz's critique of the Abecedarian Project. Intelligence, 17, 31-35.

Spitz, H. H. (1993b). When prophecy fails: On Ramey's response to Spitz's critique of the Abecedarian Project. Intelligence, 17, 17-23.

Sternberg, R. J., & Wagner, R. K. (1993). The g-ocentric view of intelligence and job performance is wrong. Current Directions in Psychological Science, 2, 1-5.

Thorndike, R. L.(1984). Intelligence as information processing: The mind and the computer. Bloomington, IL: Center on Evaluation, Development, and Research.

Watkins, M., Lei, P. W., & Canivez, G. L. (2007). Psychometric intelligence and achievement: A cross-lagged panel analysis. Intelligence, 35, 59-68.

Labels: education, general intelligence, IQ, jobs

Charles Murray has a three-piece series of op-eds in the WSJ. They describe education policy recommendations for three levels of the IQ distribution:

1. Intelligence in the Classroom: Half of all children are below average, and teachers can do only so much for them.
2. What's Wrong With Vocational School? Too many Americans are going to college. 
3. Aztecs vs. Greeks: Those with superior intelligence need to learn to be wise. 

The only criticism I can offer is the lack of citations/footnotes to support the many empirical claims made, especially in the first article, but I understand the venue does not permit it.

You can find plenty of criticisms on the web. At the Corner, Jonah Golderg criticizes Murray for being "dismissive of alternative or competing definitions of intelligence". Golberg's criticism is somewhat missing the mark by his framing in terms of "competing definitions of intelligence", but the IQ's corner blog offers a critique (and follow up) that appears to capture the spirit of Jonah's remark in more precise language. Jonah also confuses intelligence with wisdom -- a mistake worth pointing out. Hopefully Murray will find time to address his critics and publish a response in a venue where the underlying data can be examined more fully.

Another aspect of this worth pointing out: it is generally agreed that it is distinctly impolite to discuss differences in intelligence in public. However, this doesn't stop intelligence from being discussed in private, and is an unfortunate hamper to an important debate. In the comment threads of several recent posts we've discussed the issue of public discussion of non-PC topics. I would suggest that the intersection of intelligence and education falls into the class where the benefits of open debate far out weight the costs. As for getting over our discomfort with intelligence differences, I note that pharmaceutical companies have made major strides by getting commercials for embarrassing medical conditions onto prime time TV.

Labels: IQ

One of the papers mentioned before on the lack of association between the derived haplotypes at ASPM and Microcephalin and intelligence is now out. Here's the abstract:

Recent studies have made great strides towards identifying putative genetic events underlying the evolution of the human brain and its emergent cognitive capacities. One of the most intriguing findings is the recurrent identification of adaptive evolution in genes associated with primary microcephaly, a developmental disorder characterized by severe reduction in brain size and intelligence, reminiscent of the early hominid condition. This has led to the hypothesis that the adaptive evolution of these genes has contributed to the emergence of modern human cognition. As with other candidate loci, however, this hypothesis remains speculative due to the current lack of methodologies for characterizing the evolutionary function of these genes in humans. Two primary microcephaly genes, ASPM and Microcephalin, have been implicated not only in the adaptive evolution of the lineage leading to humans, but in ongoing selective sweeps in modern humans as well. The presence of both the putatively adaptive and neutral alleles at these loci provides a unique opportunity for using normal trait variation within humans to test the hypothesis that the recent selective sweeps are driven by an advantage in cognitive abilities. Here, we report a large-scale association study between the adaptive alleles of these genes and normal variation in several measures of IQ. Five independent samples were used, totaling 2,393 subjects, including both family-based and population-based datasets. Our overall findings do not support a detectable association between the recent adaptive evolution of either ASPM or Microcephalin and changes in IQ. As we enter the post-genomic era, with the number of candidate loci underlying human evolution growing rapidly, our findings highlight the importance of direct experimental validation in elucidating their evolutionary role in shaping the human phenotype.

Labels: IQ

A new La Griffe is up: Intelligence, Gender and Race.

Inspired by Jackson and Rushton (Intelligence 34 (2006) 479-486), La Griffe (Prodigy?) seeks to use a version of the "method of thresholds" to estimate the female distribution of g relative to males. The details are well spelled out in the article. Combining a variety of data sources, the article arrives at a least-squares estimate of the parameters defining the distribution of g first for blacks and then for women.

A white-black mean difference in g of 1.09 SD exists in favor of whites, equivalent to 16 IQ points. The black g distribution is narrower than the white, with a variance ratio (B/W) of 0.888.

A male-female mean difference in g of 0.164 SD exists in favor of men, equivalent to 2.46 IQ points. The female g distribution is narrower than the male, with a variance ratio (F/M) of 0.916.

Contrast the sex-difference estimate with Jackson and Rushton's estimate of 3.63 IQ points. At the time of publication of the Jackson and Rushton paper, I noted that no attempt was made to take into account the very well documented difference in variability of IQ between men and women. We can now compare Jackson and Rushton's estimate with La Griffe's. Above a +1 sd threshold, women would make up only 40% of the population using Jackson and Rushton's estimate and assuming equal variance. Notably, using La Griffe's estimates of mean and variance, women would make up 39% of the population above a +1 SD threshold.

Even small differences in mean and variance can have large effects at the tails. To give an idea of the effects, I've generated a table listing the percentage of women in a population above +1 SD for values of female mean in standard units (listed in the first column) and the ratio of female to male SDs (listed in the first row).

	1	0.975	0.95	0.925	0.916	0.9	0.875	0.85
0	50%	49%	48%	47%	46%	46%	44%	43%
-0.025	49%	48%	47%	46%	45%	45%	43%	42%
-0.05	48%	47%	46%	45%	44%	43%	42%	41%
-0.075	47%	46%	45%	44%	43%	42%	41%	39%
-0.1	46%	45%	44%	42%	42%	41%	40%	38%
-0.125	45%	44%	43%	41%	41%	40%	38%	37%
-0.15	44%	43%	42%	40%	40%	39%	37%	36%
-0.164	44%	42%	41%	40%	39%	38%	37%	35%
-0.175	43%	42%	41%	39%	39%	38%	36%	34%
-0.2	42%	41%	39%	38%	37%	37%	35%	33%
-0.225	41%	40%	38%	37%	36%	35%	34%	32%
-0.242	40%	39%	38%	36%	36%	35%	33%	31%
-0.25	40%	39%	37%	36%	35%	34%	33%	31%
-0.275	39%	38%	36%	35%	34%	33%	31%	30%
-0.3	38%	37%	35%	34%	33%	32%	30%	28%

Labels: IQ

Count 'em: one, two, three new studies on the relationship between IQ and academic achievement in the latest issue of Intelligence (volume 35, issue 1)

Before the studies' precis, a little background on why such studies are necessary. More than anything, such studies are needed because folks such as S. Ceci and R. Sternberg (very prominent and oft-cited) advocate that (traditional) IQ tests are just measuring little more than school related achievement. So, IQ and academic achievement are only related because, for reasons X, Y, and Z (pick your own environmental variables), some folks get more out of school, and it just so happens that the same folks do well on IQ tests due largely (if not entirely) because school achievement and IQ tests are measuring the same thing. Consequently, g is an irrelevant artifact of those damned psychometricians.

An alternative hypothesis (explicated nicely in Jensen^1,2), however, is that due largely to genetic factors (which influence both individual differences and environmental influences), people enter school with wide variability in cognitive ability and "readiness to learn." This initial variability then heavily influences (although not completely determines) the amount a given student will pick up as he/she matriculates. As a student gains more information, his/her initial ability and the new information acquired then interact so he/she is able to expand his/her knowledge further, and so on and so forth. Therefore, while one needs access to "information," the child's general cognitive ability is the engine driving his/her educational achievement.

Don't miss the point here. These are two separate, testable, hypotheses. (A) IQ and academic achievement are synonymous. That is, people are smart (or not so smart) almost solely because they had (or did not have) a good education. (B) IQ is independent of academic achievement, although the former significantly influences the latter. That is, you can come from a good school, but not be so bright, and do poorly on achievement tests; likewise, you can come from a school that is not so good, (but meets some very minimum standard), but be bright, and do very well on academic achievement tests.


Now, the studies.......


1) Treena Eileen Rohde and Lee Anne Thompson: Predicting academic achievement with cognitive ability

This study is likely the weakest only because they used a group of college students from an elite university. Not that there is anything wrong with this, but when you see the samples in the studies below, it is a noticeable concern.

Their major contribution was that in predicting (standardized) academic achievement, speed of information processing and spatial ability can explain small, but significant, amounts of variance unexplained by general vocabulary (Mill Hill) and perceptual organization (Raven's Matrices), although the latter two tests, hands down, did the best in predicting academic achievement across various indicators.

In their own words:

General cognitive ability measures (Raven's, Vocabulary) and specific cognitive abilities (working memory, processing speed, spatial ability) collectively accounted for between 16% [GPA] and 54% [SAT] of the variance in academic achievement.

2) Marley W. Watkins, Pui-Wa Lei and Gary L. Canivez: Psychometric intelligence and achievement: A cross-lagged panel analysis

This study had 3 advantages over the former: (1) it is longitudinal, (2) the data is from a much wider scope of IQs, and (3) the data comes from all over the US. The drawback, and major caveat, is that the data is all from special education (broadly defined) testing, so the applicability to the entire population is in question. Still, the mean Full Scale IQ score from the WISC-III (the IQ instrument used) is 90 with a SD of 15 (in the general population it is 100 and 15), and the subtest scores hover around 8 with SDs that hover around 3 (in the general population it is 10 and 3).

Because they have longitudinal data on both standardized IQ and standardized achievement tests, they can specifically test the IQ--->Achievement hypothesis (see preamble). What do they find?

This notion of intelligence estimating a student's ability to succeed in school assumes the temporal precedence of intelligence to achievement. . . Regardless, the present study supports the view that intelligence, as measured by the VC [Verbal Comprehension] and PO [Perceptual Organization] dimensions of the WISC-III, influences or is related to future achievement whereas reading and math achievement do not appear to influence or are not related to future psychometric intelligence.

Stated more bluntly:

. . . the present study provides evidence that psychometric intelligence is predictive of future achievement whereas achievement is not predictive of future psychometric intelligence. This temporal precedence is consistent with the theoretical position of Jensen (2000)[¹] that intelligence bears a causal relationship to achievement and not the other way around.

3) Ian J. Deary, Steve Strand, Pauline Smith and Cres Fernandes: Intelligence and educational achievement

Before getting on to the study, a brief word about Dr. Deary. He is the current badass of differential psychology. Because of his background (degrees in medicine and psychology), he is able to investigate psychometric, chronometric, genetic, and neurological aspects (often concurrently) of both intelligence and personality (look at the range on his vita). As if that were not enough, he has challenged the whole field of differential psychology by obtaining multiple population level, longitudinal data sets. So instead of trying to infer from a sample a few hundred to the target population, he is gathering population level samples of thousands of individuals. Case in point:

Deary's study looked at how cognitive ability measured at age 11 predicted academic achievement at age 16. Unsurprisingly, the IQ-Achievement correlations for the Sciences are around .6 (math highest, chemistry lowest), with similar coefficients form Arts/Humanities and Social Studies. Surprisingly, for practical fields (e.g., P.E., Art) the coefficients are a little lower, but not that much, averaging around .5. Here is a pic of the correlation table: (the n is in parentheses; it obviously changes as not every student took every class)




Deary took the analysis a step further however and did a little latent variable modeling. As the IQ test had three components/subtests (verbal, nonverbal, quantitative), he correlated a latent g factor with a latent academic factor using the following subtests: English, English Literature, Math, Science, Geography, French (n=12519). The correlation between the latent factors was .81. That is: 66% of the variance in latent (general) academic achievement can be explained by latent cognitive ability---measured 5 years previously. While he hypothesizes that such things as "school ethos" and "parental support" are good areas to search for the other 34%, based on Rohode's work, it is likely going to be found in residual, first order factors (see Carroll or McGrew).

Take home message: While general cognitive ability and academic achievement are not isomorphic, the former is necessary for the latter, while the converse is not necessarily true. Spearman suggested this more than a century ago, and, to quote the last sentence in Deary's work,

These data establish the validity of g for this important life outcome.

1. Jensen, A. R. (2000, August). The g factor and the design of education. Paper presented at the annual meeting of the American Psychological Association, Washington, DC.

2. Jensen, A. R. (1989). The relationship between learning and intelligence. Learning and Individual Differences, 1, 37-62.

Labels: IQ

Here is my general model. Ignore the magnitude of the slope, I suspect the covariance between IQ & hotitude is rather modest indeed. Nevertheless, the graph illustrates my general model, a linear increase between 85 and 115, about 75% of the population. Then, a slight linear decrease up the IQ ladder (though beyond 140 you don't have too many people). Finally, below 85, and definitely below 75, a much sharper drop in attractiveness, and increase in phenotypic variance due to macroscale developmental instability.

Labels: IQ

Low IQ is a risk factor for developing schizophrenia, though the mechanism behind this association is somewhat unclear. A new study sheds a little light on this subject, and suggests the link might be genetic. The gene in questions is neuregulin 1, about which little is known. They find, first, that a regulatory SNP is associated with the development of psychotic symptoms in a particularly at-risk population (see part a above-- each bar is the percentage of subjects developing symptoms for a given genotype). They also find lower levels of activity in certain part of the brain in the patients with the TT genotype (see parts b and c above).

Further, here are the means and standard deviations of the IQ distributions of the different genotypes:

CC: 101.9 (8.4)
CT: 100.4 (9.4)
TT: 94.3 (6.9)

So this regulatory polymorphism could explain some of the natural variation in IQ.

Labels: disease, IQ

A question from Jason Malloy prompted a quick search of the GSS for data on the cause of the Black-White IQ gap. In 1982, the GSS characterized the skin color of Black participants on a 5-point scale (1:very dark brown to 5:very light brown). The very dark/light categories consist of only 50 and 14 individuals, respectively, and so in the following analysis I merged them with the dark/light brown categories, to give three COLOR levels: dark, medium, and light. In the web application, use COLOR(r:1-2;3;4-5) instead of COLOR. The WORDSUM variable is a 10 question vocabulary test, which I'm treating as a proxy for IQ. It is correlated with educational attainment (~.4), and also correlates (~.4-.5) with tests of reasoning and basic knowledge that were given in some years. These other tests are not available for 1982. In the all-subject all-year GSS data set, WORDSUM varies by SEX, and in 1982 COLOR also varies by SEX. Thus, SEX is controlled for in each analysis. WORDSUM is lower in the youngest and oldest age groups, so an AGE(25-65) filter was used.

Table 1. Mean WORDSUM score by COLOR and SEX with ANOVA

Main Statistics
Cells contain: -Means -Std Devs -N of cases		SEX
		1 MALE	2 FEMALE	ROW TOTAL
COLOR	1: Dark	4.15 1.964 56	4.52 1.709 56	4.35 1.833 112
	2: Medium	5.39 2.314 61	5.14 2.164 96	5.23 2.218 157
	3: Light	6.04 1.860 17	5.58 2.254 41	5.70 2.153 58
	COL TOTAL	4.97 2.224 134	5.06 2.088 193	5.02 2.139 327

color indicates T-statistic, and thus p-value

Color coding:	<-2.0	<-1.0	<0.0	>0.0	>1.0	>2.0	T
Mean in each cell:	Smaller than average			Larger than average

Analysis of Variance
	SSQ	Eta_sq	df	MSQ	F	P
Main effects	89.443	.061	3	29.814	6.956	.0002
COLOR	89.099	.061	2	44.549	10.394	.0000
SEX	.691	.000	1	.691	.161	.6884
Interaction	2.569	.002	2	1.285	.300	.7412
Residual	1,375.884	.937	321	4.286
Total	1,467.896	1.000	326

We can quantify the effect size of each skin color class using Cohen's d statistic, which measures the mean difference in standard deviation units. In the 1982 dataset, the overall d for the Black-White gap on WORDSUM is -0.63 (among males d=-0.51, among d=-0.74). For comparison, the 1982 male-female gap among Whites is d=-.12, favoring females.

Table 2. Effect size (d) of COLOR on WORDSUM using "light" as a control group

Color	Male	Female	Total
Dark	-0.99	-0.53	-0.68
Medium	-0.31	-0.20	-0.22
Light	0.00	0.00	0.00

We can also use Whites as the control group.

Table 3. Effect size (d) of COLOR on WORDSUM using Whites as a control group

Color	Male	Female	Total
Dark	-0.99	-1.10	-1.04
Medium	-0.35	-0.69	-0.54
Light	-0.07	-0.46	-0.33

Thus, there are substantial (moderate to large effect size) differences in WORDSUM scores between the darkest and lightest Blacks in 1982.

As reported by Rushton and Jensen (2005), Shuey (1966) reviewed 18 studies which used skin color as a measure of racial admixture to compare with IQ. Of those 18, 16 found a significant effect of the kind found here, but the overall correlation with IQ was low (r=.1). In this data, the COLOR WORDSUM correlation is r=.31 among males and r=.18 among females, with an overall correlation of r=.23. Off the top of my head, I'm not certain what the expected correlation would be between IQ and skin color among Blacks for a given measure of "between-group heritability" (BGH) as described by Jensen (1998). I'll leave it as an exercise for our mathematically skilled commentators to derive a formula for this relationship and to evaluate the signficance of this finding in explaining the cause of the Black-White IQ gap.

Labels: Economics, GSS, IQ, Pigmentation, race

Some of you may have read the recent news report of a paper by William Flynn and James Flynn arguing that the white-black IQ gap has steadily narrowed over the last 30 years. I believe that this paper, as well as a rebuttal by Phillipe Rushton and Arthur Jensen, will be published in an upcoming issue of Psychological Science.

Our own resident educational psychologist Alex Beajuean is analyzing these and other relevant data using a model-based approach that is more sophisticated than the techniques used by Dickens and Flynn. We may deliver a report here at GNXP when this analysis is done. In the meantime, we have made a little graph showing the results of the studies conducted during the period covered by Dickens and Flynn, including those studies that Dickens and Flynn omitted from their analysis (and that Rushton and Jensen argue should have been included):


As you can see, the gap between white and black children does indeed seem to be decreasing over time. The gap between adults, however, does not show any noticeable trend. Perhaps the adults are lagging behind a true gain by blacks as a whole, but remember also that the correlation between genotypic and phenotypic IQ increases with age. Without further analysis, I suggest simply keeping this graph in mind as we go forward.

Labels: IQ

Bloggers Half Sigma and Inductivist are having ongoing fun with the General Social Survey data set: ethnic, gender, and religious comparisons galore! Half Sigma looks at the relationship between the GSS mini-IQ test and religious belief, and finds what we already knew.

Labels: IQ