Razib Khan One-stop-shopping for all of my content

August 17, 2011

Looking for a few good 145+ I.Q. individuals

Above is the distribution of self-reported I.Q.s of the readers of this weblog according to the 2011 survey. I point this out because my friend Steve Hsu will be giving a talk at Google later today. Here are the details:

I’ll be giving a talk at Google tomorrow (Thursday August 18) at 5 pm. The slides are here. The video will probably be available on Google’s TechTalk channel on YouTube.

The Cognitive Genomics Lab at BGI is using this talk to kick off the drive for US participants in our intelligence GWAS. More information at www.cog-genomics.org, including automatic qualifying standards for the study, which are set just above +3 SD. Participants will receive free genotyping and help with interpreting the results. (The functional part of the site should be live after August 18.)

Title: Genetics and Intelligence

Abstract: How do genes affect cognitive ability? I begin with a brief review of psychometric measurements of intelligence, introducing the idea of a “general factor” or IQ score. The main results concern the stability, validity (predictive power), and heritability of adult IQ. Next, I discuss ...

May 13, 2011

I.Q. and genomics

Filed under: B.G.I.,Behavior Genetics,Genomics,I.Q.,Psychology,Psychometrics — Razib Khan @ 9:15 pm

In my experience most scientists are not too clear on the details of intelligence testing, perhaps because the whole area is somewhat in ill repute (except when you want to brag about your own SAT/GRE score!). This despite the fact that the profession of science is skewed toward the right end of the intelligence bell curve. Steve Hsu, a physicist at the University of Oregon (and someone I’ve known for a while in the interests of “full disclosure”) has a nice presentation up in PDF format which summarizes the major points of interest in this area. Worth a skim if you are unfamiliar. Additionally he alludes to future directions in the study of the genetic basis of intelligence using genomics. Here’s his abstract:

I begin with a brief review of psychometric results concerning intelligence (sometimes referred to as the g factor, or IQ). The main results concern the stability, validity (predictive power) and heritability of adult IQ. Next, I discuss ongoing Genome Wide Association Studies which investigate the genetic basis of intelligence. Due mainly to the rapidly decreasing cost of sequencing (currently below $5k per genome), it is likely that within the next 5-10 years we will identify genes ...

September 27, 2010

American family values: where even the dull can dream!

ResearchBlogging.orgOne of the issues when talking about the effect of environment and genes on behavioral and social outcomes is that the entanglements are so complicated. People of various political and ideological commitments tend to see the complications as problems for the other side, and yet are often supremely confident of the likely efficacy of their predictions based on models which they shouldn’t even been too sure of. That is why cross-cultural studies are essential. Just as psychology has overly relied on the WEIRD nature of data sets, so it is that those interested in social science need to see if their models are robust across cultures (I’m looking at you economists!).

That is why this ScienceDaily headline, Family, Culture Affect Whether Intelligence Leads to Education, grabbed my attention. The original paper is Family Background Buys an Education in Minnesota but Not in Sweden:

Educational attainment, the highest degree or level of schooling obtained, is associated with important life outcomes, at both the individual level and the group level. Because of this, and because education is expensive, the allocation of education across society is an important social issue. A dynamic quantitative environmental-genetic model can help document the effects of social allocation patterns. We used this model to compare the moderating effect of general intelligence on the environmental and genetic factors that influence educational attainment in Sweden and the U.S. state of Minnesota. Patterns of genetic influence on educational outcomes were similar in these two regions, but patterns of shared environmental influence differed markedly. In Sweden, shared environmental influence on educational attainment was particularly important for people of high intelligence, whereas in Minnesota, shared environmental influences on educational attainment were particularly important for people of low intelligence. This difference may be the result of differing access to education: state-supported access (on the basis of ability) to a uniform higher-education system in Sweden versus family-supported access to a more diverse higher-education system in the United States.


Minnesota is to some extent the Scandinavia of America, so the cross-cultural difference is particularly notable. You wouldn’t be surprised for example by big differences between Mississippi and Sweden. But looking at a comparison between the Upper Midwest and Scandinavia is closer to seeing the impact of national culture and policy differences on populations which were originally very similar.

Their methodology was simple, though as with much of this sort of behavior genetic work the statistical analysis can be somewhat labored. In both Sweden and Minnesota you had samples of dizygotic and monozygotic twins which give you a way to compare the effect of genes on variation in life outcomes. Sweden has large data sets from male conscription for behavior genetics analysis. They compared this with the Minnesota Twin Family Study data set.

Since the topline results are pretty straightforward, I thought I’d give you some statistics. Table 1 has raw correlations. Note that they converted educational attainment into a seven-point scale, less than 9 years of education to completion of doctoral studies.

swed1

You see the expected drop off in correlation between identical and fraternal twins. Identical twins share more genetic identity than fraternal twins, so they’re going to be more identical on a host of metrics aside from appearance. Those are just raw correlation values of traits though across categories of twins. The core intent of the paper was to explore the relationship between genes, family environment, and other environmental factors, and educational attainment. To do this they constructed a model. Below you see estimates of the variance in the trait explained by variance in genes, shared environment (family), non-shared environment (basically “noise” or error, or it could be something like peer group), from Sweden to Minnesota, and, at three intelligence levels. Two standard deviations below the norm is borderline retarded, ~2.5% of the population or so, and two standard deviations above the norm is at Mensa level.

swed2

It’s interesting that as you move up the IQ scale the genetic variation explains more and more of variance the educational attainment. Someone with an IQ of 130 is likely to be university educated. But there are many who are not. Why? The way I interpret these results is that if you are that intelligent and do not manage to complete university you may have heritable dispositions of personality which result in you not completing university. If, for example, you come from a family which is very intelligent, but is low on conscientiousness, then there may be a high likelihood that you just won’t complete university because you can’t be bothered to focus. Or, you may have personality characteristics so that you don’t want to complete university. A second major finding here is that Sweden and the USA go in totally different directions when it comes to the sub-average and dull in prediction of years of education. Why? The explanation in the paper seems plausible: Sweden strongly constrains higher education supply, but makes it available to those with proven academic attainments at a nominal price. Family encouragement and connections don’t matter as much, if you can’t pass the university entrance examination you can’t pass it. In contrast in the USA if you’re dull, but come from a more educated or wealthier family, you can find some university or institution of higher education which you can matriculate in. Supply is more flexible to meet the demand. I actually know of a woman who is strongly suspected to be retarded by her friends. I have been told she actually tested in the retarded range in elementary school but was taken out of that  track because her family demanded it (she’s the product of a later conception, and her family made their money in real estate, not through professional advancement). Over the years she has enrolled in various community colleges, but never to my knowledge has she completed a degree. If she had not had family connections there is a high probability she wouldn’t have completed high school. As it is, she can check off “some college” on demographic surveys despite likely be functionally retarded.

The next table is a bit more confusing. It shows you the correlations between the effects of the variable on education and intelligence. In other words, does a change in X have the same directional effect on Y and Z, and what is the extent of the correspondence between the effect on Y and Z.

swed3

Shared environment had almost the same effect on intelligence and education, while genetics had a more modest simultaneous effect. Not too surprising that non-shared environment didn’t have a strong correlation in effect across the traits, the authors note that much of this is going to noise in the model, and so not systematically biased in any direction. Though the confidence intervals here are a little strange. I’m not going to get into the details of the model, because frankly I’m not going to replicate the analysis with their data myself. That’s why I wanted to present raw correlations first. That’s pretty straightforward. Estimates of variances out of models with a set of parameters is less so. Here’s an interesting point from the correlations in the last table:

The patterns of genetic correlations in the two samples differed. In Sweden, genetic correlation was steadily in excess of .50 across the range of intelligence, indicating a genetically influenced direct effect of intelligence on educational attainment that was weaker than the shared environmental effect on educational attainment. In the MTFS [Minnesota] population, however, genetic correlation was in excess of .50 when level of intelligence was low, but was halved at higher levels of intelligence. This indicated that genetic influences on intelligence tended to limit educational attainment when the level of intelligence was low, but not when the level of intelligence was average or high.

Now let me jump to conclusion:

This finding indicates that genetic influences common to intelligence and educational attainment may have been more effective in limiting educational attainment in individuals with low levels of intelligence than in encouraging educational attainment in those with high levels of intelligence. As in Sweden, shared environmental influences on intelligence and educational attainment were completely linked, indicating a direct contribution from shared environmental influences on intelligence to educational attainment. The decrease in shared environmental variance with higher intelligence, however, indicated that shared environmental influences were more effective in encouraging educational attainment in higher-intelligence individuals than in limiting educational attainment in lower-intelligence individuals. In other words, in populations in which shared environmental influences such as family history and values encouraged high levels of educational attainment, individuals were able to surmount limitations in intelligence.

Our analysis does not permit the conclusion that these differences in educational systems cause the differences in environmental and genetic influences on educational attainment observed in this study, but it is reasonable to hypothesize that this is likely. In particular, the greater expense of higher education and greater subjectivity of admission standards in the United States compared with Sweden may partially explain the very different patterns of shared environmental influences in the two population samples. Regardless of the causes underlying the differences we observed, the results of our study make clear that the degrees of environmental and genetic influences can vary substantially between groups with different circumstances, and even within such groups. Our results also suggest that the ways in which social systems are organized may have implications for how and to what extent environmental and genetic influences on behavior will be expressed.

This discussion about the role of environment, genes, and culture, on various outcomes should not hinge on one paper. But, these sorts of results are often not widely disseminated among the intellectual classes. One aspect of the American educational system in contrast to some other nations is that not-too-brights have university degrees. Education has long been a project for social engineering in the USA, going back to Horace Mann. Legacies, underrepresented minorities, the poor, those with particular talents, etc., are all part of the decentralized system of university admissions in the United States. In contrast, in nations such as Sweden or Japan there is a more centralized and universal set of criteria. This results is more perfect sorting by the metrics of interest without considerations of social engineering. I know that Sweden has traditionally had a small aristocratic class, while the Japanese aristocracy were basically abolished after World War II. Additionally, both are relatively homogeneous societies so considerations of racial representativeness are not operative. Or weren’t until recently in the case of Sweden. But consider one reality: if such a system is perfectly meritocratic over time if the traits being evaluated are heritable then you will have genetic stratification and reduction of social mobility assuming assortative mating at university.

Currently there is some handwringing by the elites about the fact that so few poor kids get admitted to Ivy League universities. I think there’s a simple way to change this: get rid of the implicit Asian quotas. After all, there was a lot of socioeconomic diversity after the Ivy League universities got rid of their Jewish quotas, but the children of the Jews who didn’t have to go to CUNY and went to Harvard are well off themselves. But more socioeconomic mobility through removing the implicit Asian quota would cause other difficulties, as elite private universities need their slots for both legacies as well as underrepresented minorities for purposes of social engineering/fostering diversity/encouraging donations. Additionally, just as with the Jews the welter of mobility in one generation of the children of Asian immigrants would settle into quiescence in the next if the traits which enable university admission are genetically or culturally heritable.

Citation: Johnson W, Deary IJ, Silventoinen K, Tynelius P, & Rasmussen F (2010). Family background buys an education in Minnesota but not in Sweden. Psychological science : a journal of the American Psychological Society / APS, 21 (9), 1266-73 PMID: 20679521

June 27, 2010

Psychometrics, epigenetics and economics

Filed under: IQ,Psychology,Psychometrics — Razib Khan @ 10:26 am

Two papers of interest. IQ in the Production Function: Evidence from Immigrant Earnings (ungated). And Human Intelligence and Polymorphisms in the DNA Methyltransferase Genes Involved in Epigenetic Marking. My impression is that the focus on epigenetics has a higher-order social motive; even the sort of humanists who are involved with N + 1 have asked me about the topic. But how many people know what methylation is?

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