thanks! 
 
the last in our time was great. i feel inclined to learn more about group theory now.

http://en.wikipedia.org/wiki/Brenda_Ann_Spencer

A pubmed search will turn up a number of putative genetic associations for IQ. One has to be cautious about these reports -- not because of IQ but because genetic associations are notoriously prone to false positives. A recent study was unable to confirm any of 85 putative associations with heart disease: 
A study looking at 85 genetic variations thought to be linked to heart disease ? some of which are already used in clinical tests ? has been unable to confirm that any of these links are real.  
However, at least one IQ association has been corroborated by multiple studies. As the power of genetic association studies improves, we can expect more.

Implications. Estimates of h2 and c2 for IQ (or any other trait) are descriptive statistics for the populations studied. (In this respect they are like means and standard deviations.) They are outcome measures, summarizing the results of a great many diverse, intricate, individually variable events and processes, but they can nevertheless be quite useful. They can tell us how much of the variation in a given trait the genes and family environments explain, and changes in them place some constraints on theories of how this occurs. On the other hand they have little to say about specific mechanisms, i.e. about how genetic and environmental differences get translated into individual physiological and psychological differences. Many psychologists and neuroscientists are actively studying such processes; data on heritabilities may give them ideas about what to look for and where or when to look for it. 
 
A common error is to assume that because something is heritable it is necessarily unchangeable This is wrong. Heritability does not imply immutability. As previously noted, heritable traits can depend on learning, and they may be subject to other environmental effects as well. The value of h2 can change if the distribution of environments (or genes) in the population is substantially altered. On the other hand, there can be effective environmental changes that do not change heritability at all. If the environment relevant to a given trait improves in a way that affects all members of the population equally, the mean value of the trait will rise without any change in its heritability (because the differences among individuals in the population will stay the same). This has evidently happened for height: the heritability of stature is high, but average heights continue to increase (Olivier, 1980). Something of the sort may also be taking place for IQ scores the so-called 'Flynn effect" discussed in Section IV. 
 
In theory, different subgroups of a population might have different distributions of environments or genes and hence different values of h2. This seems not to be the case for high and low IQ levels, for which adult heritabilities appear to be much the same (Saudino, Plomin, Pedersen, & McClearn, 1994). It is also possible that an impoverished or suppressive environment could fail to support the development of a trait, and hence restrict individual variation. This could affect estimates of h2, c2, Or both, depending on the details of the process. Again (as in the case of whole populations), an environmental factor that affected every member of a subgroup equally might alter the group's mean without affecting heritabilities at all. 
 
Where the heritability of IQ is concerned, it has sometimes seemed as if the findings based on differences between group means were in contradiction with those based on correlations. For example, children adopted in infancy into advantaged families tend to have hi
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Neisser et al (1996) wrote: 
 
Parameter Estimates. Across the ordinary range of environments in modern Western societies, a sizable part of the variation in intelligence test scores is associated with genetic differences among individuals. Quantitative estimates vary from one study to another, because many are based on small or selective samples. If one simply combines all available correlations in a single analysis, the heritability (h2) works out to about .50 and the between-family variance (c2) to about .25 (e.g., Chipuer, Rovine, & Plomin, 1990; Loehlin, 1989). These overall figures are misleading, however, because most of the relevant studies have been done with children. We now know that the heritability of IQ changes with age: h2 goes up and c2 goes down from infancy to adulthood (McCartney, Harris, & Bernieri, 1990; McGue, Bouchard, Iacono, & Lykken, 1993). In childhood h2 and C2 for IQ are of the order of .45 and .35; by late adolescence h2 is around .75 and c2 is quite low (zero in some studies). Substantial environmental variance remains, but it primarily reflects within-family rather than between-family differences. 
 
These adult parameter estimates are based on a number of independent studies. The correlation between MZ twins reared apart, which directly estimates h2, ranged from .68 to .78 in five studies involving adult samples from Europe and the U.S. (McGue et al., 1993). The correlation between unrelated children reared together in adoptive families, which directly estimates c2, was approximately zero for adolescents in two adoption studies (Scarr & Weinberg, 1978; Loehlin, Horn, & Willerman, 1989) and .19 in a third (the Minnesota transracial adoption study: Scarr, Weinberg & Waldman, 1993). 
 
These particular estimates derive from samples in which the lowest socioeconomic levels were underrepresented (i.e., there were few very poor families), so the range of between family differences was smaller than in the population as a whole. This means that we should be cautious in generalizing the findings for between-family effects across the entire social spectrum. The samples were also mostly white, but available data suggest that twin and sibling correlations in African-American and similarly selected White samples are more often comparable than not (Loehlin, Lindzey, & Spuhler, 1975). 
 
Why should individual differences in intelligence (as measured by test scores) reflect genetic differences more strongly in adults than they do in children's One possibility is that as individuals grow older their transactions with their environments are increasingly influenced by the characteristics that they bring to those environments themselves, decreasingly by the conditions imposed by family life and social origins. Older persons are in a better position to select their own effective environments, a form of genotype-environment correlation. In any c
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one more: 
 
iirc, Flynn is not very keen on the nutritional hypothesis for the Flynn effect, at least for gains in the 2nd half of 20c.

if someone can find the references for these, here are a few tid-bits from memory: 
 
* the height-IQ correlation is not found within families, and thus appears to be due to assortative mating 
* nutritional deprivation has a complex relationship to IQ, but some kinds of strong deprivation can have very little lasting effects (i.e. they are remediable); not sure about the comparable effects on height - a period of famine in euro during 20c (i think ca WWII) provides data for this as does East Asian adoption data 
* according to the latest papers from Flynn, he doesn't think the Flynn effect has an impact on g, and thus the most-heritabile component of IQ scores are qualitatively different than the intergeneration change 
* a heritabiltiy of 70%-80% among adults living in middle class, Western environments is now a consensus; the "range" in reported heritabilities is largely due to the fact that heritability increases with age (i.e. heritability is seemingly lower at younger ages)

here's a stem-and-leaf plot of the results so far 
 
0 | 12 
0 | 559999 
1 | 134444 
1 | 56667777 
2 | 122

16 
 
extreme focus helps me ignore sensory disturbances; otherwise they are noisome (then I'd score 22)

thanks -- 
 
"Models 1 and 2 imply very different interpretations of changes in the B?W difference on the Woodcock?Johnson." 
 
this is where i got tripped up. 
 
it makes more sense realizing that the difference in the models is just a matter of censoring some of the data.

i read through once quickly. can someone explain the difference between model 1 and model 2?

with the passage of time, my confidence in the veracity of the published science literature decreases. 
 
i think a little AI fact and logic checking would go a long way.

from wikipedia, on cousin matings: 
 
In April 2002, the Journal of Genetic Counseling released a report authored by a team of scientists led by Robin L. Bennett, a genetic counselor at the University of Washington and the president of the National Society of Genetic Counselors, which showed that the potential risk of birth defects in a child born of first cousins was slightly higher than the risk associated with a non-cousin couple. The report estimated the increased risk for first cousins is only between 1.7 to 2.8 percent on top of the base risk of about 5%, or about the same as any woman over 40 years of age. To put it another way, first-cousin marriages entail roughly the same increased risk of abnormality that a woman undertakes when she gives birth at 41 (roughly 8%) rather than at 30 (roughly 5%). Banning cousin marriages makes about as much sense, critics argue, as trying to ban childbearing by older women. 
 
of course, this is for single inbreeding events, compared to the repeated inbreeding that occurs in some cultures.

society has better things to be punishing people for than such rare and unusual matings 
 
i would expand on that. because adult-onset incest is usually the result (rather than the cause) of having a fucked up life, it makes little sense to make these people's lives worse by imprisoning them.

s/wall/membrane/

deceit or obfuscation -- different only by degrees I would argue. it's a serious problem for public discourse about contemporary science.

if anyone is up to it, it would be worth comparing their geographic controls with what Rosenberg et al. found http://dx.doi.org/10.1371/journal.pgen.0010070

did they publish their data somewhere?

how many SAGE tags could you quantify with 600e6 or 100e9 bp of sequence?

single molecule separation and then sequencing?