Chinese (Taiwanese) find neurological g-factor, possibly

While the existence of a psychometric g is now firmly established, there is considerable controversy concerning the existence of a neurological and/ or genetic g. (See my previous post.) For those not familiar with the debate, let me just quote from Ian Deary’s excellent recent article, Intelligence:

Probably the strongest psychometric challenge to Spearman’s account of intelligence differences was from Godfrey Thomson (Bartholomew et al. 2009). Thomsonever denied Spearman’s positive manifold of correlations among mental tests, but he suggested a radically different reason for its occurring. Instead of g—perhaps, according to Spearman, the result of people having generally more or less of mental energy or power — Thomson found that the universally positive correlations among tests could also arise from each test’s sampling a subset of numerous, independent mental bonds; thus his “bonds” or “sampling” theory of intelligence. The Spearman-Thomson debates lasted from the First World War until almost the end of World War II. A fresh look at Thomson’s ideas concluded that his model of intelligence was not inferior to Spearman’s, either on statistical or biological grounds, though that was partly because both were vague biologically (Bartholomew et al. 2009). A related development is the mutual interaction model of intelligence, which also posits the emergence of a general factor without a general cause (van der Maas et al. 2006). The basic idea is that a statistical g emerges through the mutual interaction, over the course of their development, of several cognitive processes.

As Spearman’s model and that proposed by van der Maas et al. have radically different implications for individual (and group) differences, both with regards to their origin and stability, this issue is not an arcane one.

Lee et al., 2012. A smarter brain is associated with stronger neural interaction in healthy young females: A resting EEG coherence study

General intelligence, the g factor, is a major issue in psychology and neuroscience. However, the neural mechanism of the g factor is still not clear. It is suggested that the g factor should be non-modular (a property across the brain) and show good colinearity with various cogni- tive tests. This study examines the hypothesis that functional connectivity may be a good can- didate for the g factor. We recorded resting state eyes-closed EEG signals in 184 healthy young females. Coherence values of 38 selected channel pairs across delta, theta, alpha, beta and gamma frequencies were correlated with six intelligence quotient (IQ) subtests, including symbol search, block design, object assembly, digit span, similarity and arithmetic. A three- stage analytic flow was constructed to delineate common (g factor) and unique neural compo- nents of intelligence. It is noticed that the coherence pattern demonstrates good correlation with five of the IQ subtests (except symbol search) and non-modularity in the brain. Our com- monality analyses support connectivity strength in the brain as a good indicator of the g factor. For the digit span and arithmetic tests, the uniqueness analyses provide left-lateralized topog- raphy relevant to the operation of working memory. Performance on the arithmetic test is fur- ther correlated with strengths at left temporo-parietal and bilateral temporal connections. All the significant correlations are positive, indicating that the stronger the connectivity strengths, the higher the intelligence. Our analyses conclude that a smarter brain is associated with stronger interaction in the central nervous system. The implication and why the symbol search does not show parallel results are discussed.

A wide-ranging, sophisticated critique of biological g-theory (and with it, HBD)

KAN. 2011. THE NATURE OF NURTURE: THE ROLE OF GENE-ENVIRONMENT INTERPLAY IN THE DEVELOPMENT OF INTELLIGENCE

CHAPTER 1 Introduction
CHAPTER 2 Nonlinear epigenetic variance: Review and simulations
CHAPTER 3 The nature of nurture: On the high heritability of cultural dependent cognitive abiliies
CHAPTER 4 A genetic origin of Black-White mean IQ differences? Weak inferences based on ambiguous results
CHAPTER 5 On the interpretation of the CHC factor Gc
CHAPTER 6 The relations among g loading, heritability, and cultural load: Do current theories of intelligence account for them?
CHAPTER 7 Discussion

Kan endorses a dynamic model of g, which allows for a good degree of malleability and which makes purely environmental models of group differences more tenable. Interestingly, Kan’s characterization of g is quite similar to that of Steve Hsu (e.g., a statistical index of cognitive functioning), but Kan and Hsu draw radically different conclusions about the prospects of searching for g-genes. I think Kan draws the more valid conclusion, a conclusion which Steve missed, when he adopted his g-agnosticism. Were there no underlying biological/genetic g, searching for g-genes would be folly.

The simulations also showed that the general factor of intelligence does not have to represent a realistic (e.g. biological) common cause of individual differences. In our integrated model it is a merely a statistical entity, i.e., an informative summary descriptive. However, as such, general intelligence certainly has utility. Specifically, we consider it to be similar to ’general health’. Like general health is an informative summary descriptive of physical functioning, ’g’ is an informative summary descriptive of cognitive functioning. A distinction between g as a statistically entity, and g as interpreted as a realistic, common cause of individual differences, is not only important theoretically, but also empirically. Consider genetic association and linkage studies of intelligence, for example. So far, the search for genes for general intelligence has met with relatively little success (Deary, Johnson, & Houlihan, 2009; Plomin and Spinath, 2004; Chabris et al., in press). The alternative theories of Dickens and Flynn (2001; Dickens, 2008) and of van der Maas et al. (2006), in which the general factor of intelligence is a statistical entity originating in reciprocal beneficial interactions among cognitive processes or abilities, are able to provide a plausible explanation of this lack of success. In these theories, there are no direct genetic influences general to all abilities. If general intelligence is indeed the outcome of such interactions, the search for specific ‘genetic influences on g‘ is a questionable undertaking (Dolan, Kan, van der Maas, 2008; van der Sluis, Kan & Dolan, 2010), in particular when (1) the genetic determinants of these processes are under mutation selection balance, which means that the process of natural selection reduces genetic variance but cannot deplete all of it because new variation – due to mutations – is continually reintroduced (Penke et al., 2007), and (2) the interactions are nonlinear (e.g. Molenaar, Boomsma, & Dolan, 1993; Kan,Ploeger, Raijmakers, Dolan & van der Maas, 2011).

Anyways, if I get a chance, I will comment on chapter 4, latter.

IQ and Genetic Amplification

I was right (about this).

The increase in the heritability of intelligence may be the result of several processes. Genetic amplification has been previously suggested (DeFries et al., 1987), and this is what was observed in the present study….

….How the increase in genetic influences on intelligence is associated with developmental brain changes that occur around the period of transition from childhood to adolescence is still not fully understood. Measures for brain anatomy are under large genetic influences throughout early infancy (Gilmore et al., 2010; Smit et al., 2010), childhood and adolescence (Smit et al., 2010; Peper et al., 2009; Yoon et al., 2010; Brouwer et al., 2010; Schmitt et al., 2007; Wallace et al., 2006), and adulthood (Peper et al., 2007; Baare et al., 2001). While the genetic influences that explain individual differences in brain size seem to be generally stable at different ages, the human brain itself is a highly dynamic organ, and undergoes considerable devel- opmental changes during development from infancy up to adulthood (Giedd et al., 1999). The genetic influences found for variation in brain anatomy showed an overlap with genetic influences on intelligence in adults (Posthuma et al., 2002; Hulshoff Pol et al., 2006), and in childhood and adolescence (van Leeuwen et al., 2009; Betjemann et al., 2010; Wallace et al., 2010). The amount of brain changes in cortical thickness in adults is under genetic influences, and partly overlap with genetic influences on IQ (Brans et al., 2010). There are indications that the level of intelligence is associated with developmental trajectories of the human cortex during adolescence (Shaw et al., 2006). (Heritability of Verbal and Performance Intelligence in a Pediatric Longitudinal Sample)

I pointed out, a while back, that the overwhelming evidence of the high heritability of g and other traits has led more savvy environmentalists to reinvent themselves as GE correlationists. A GE correlational model of IQ (and other) differences is just an environmental model with a genetic veneer. So, as a result of the self-reinventions, you now frequently get “lost in correlations” bits like Flynn’s “the heritability of basketball.” Here’s an excerpt from Dickens’ article, Cognitive Ability, which makes the same point:

So how is it that large gains are possible in the face of high heritability estimates? The chief flaw in the argument that high heritability implies a limited role for environment is that it misunderstands what heritability is measuring. It ignores the possibility that genetic and environmental influences might be correlated. In particular, it ignores the possibility that genetic influences on ability are largely the work of environmental advantages that come about due to modest physiological advantages.
Consider a sports analogy.

Not infrequently, it was claimed that the increasing heritability of IQ with age supported a correlational model — heritability increases because as they age people are more and more free to seek out the cognitive niches which match their dispositions. The most plausible alternative model for this increase, which eerily often went and still goes unmentioned, is one involving genetic amplification. As for going unmentioned, take this passage from Haworth, Wright. Luciano, Martin, de Geus, van Beijsterveldt, Bartels, Posthuma, Boomsma, Davis, Kovas, Corley, DeFries, Hewitt, Olson, Rhea, Wadsworth, Iacono, McGue, Thompson, Hart, Petrill, Lubinski and Plomin (2009), which is stunning in this regards:

Why, despite life’s ‘slings and arrows of outrageous fortune’, do genetically driven differences increasingly account for differences in general cognitive ability during the school years? It is possible that heritability increases as more genes come into play as the brain undergoes its major transitions from infancy to childhood and again during adolescence. However, longitudinal genetic research indicates that genes largely contribute to continuity rather than change in g during the school years. We suggest that the developmental increase in the heritability of g lies with genotype–environment correlation: as children grow up, they increasingly select, modify and even create their own experiences in part on the basis of their genetic propensities. (The heritability of general cognitive ability increases linearly from childhood to young adulthood)

No mention of that other possible explanation for the 0.5 increase in heritability from infancy to adulthood? (Two of you did first develop the idea in the 80s.)

All of this should now be a moot point since Davies et al. (2011) has established the high narrow heritability (i.e., breeding value) of IQ. (If the high heritability or increasing heritability found in conventional twin studies was a function of (passive/evocative/active) GE correlations, as was argued, Davies et al. (2011) would have found a much lower narrow heritability in their study.) Though, the import of Davies et al. (2011) seems to have been lost on some. It is somewhat disturbing that the two dozen or so behavioral geneticists and psychometricians cited above were so off the mark with their (fairly recent) suggestion that “the developmental increase in the heritability of g lies with genotype–environment correlation.” Though, when reading the passage, one gets the feeling that they were trying to appease the environmentalist gods. Whatever the case, they were wrong and I was right.

Egalitarian Racism

Fringeelements’ newer video:

I’ve been posting on colorism and hybrid differences, in part, to elaborate on some of the technical points made by Ryan in Make the World Flat (2:48:17 on). But the whole topic ties in just as well with that of Egalitarian Racism.

The evils of Egalitarian Racism can’t be emphasized enough, given the sentiment held on our near left. Hard core progressives kid about the Rod Dreher crowd and their “only possible good…” when they discuss “biconceptualism.” The joke is that such conservatives will only be a problem until progressivism is set as the new status quo.

The unpalatableness of Egalitarian Racism needs to be drawn out, so as to make it less likely to be gulped down.

Mulatto advantage in the NLSF

I was unable to find the “parent’s race” variable in the NLSF public use data and so determine by exactly how much the mixed race Blacks outperformed their “multigenerational” peers. Apparently, this is restricted information. But I did find the following:

Black Like Who? Exploring the Racial, Ethnic, and Class Diversity of Black Students at Selective Colleges and Universities

“The National Longitudinal Study of Freshmen, was developed by Douglas Massey and Camille Charles to track the academic and social experiences of approximately 4,000 white, Asian, Latino, and black undergraduates at 28 selective colleges and universities across the country…. Included in our profile are 654 monoracial multigenerational African Americans, 197 immigrant or first-generation blacks, and 160 multiracial black students while 854 native-born white students serve as the reference group……Compared to immigrant and mixed race blacks, we find that multigenerational African Americans have the weakest academic preparation, perceive significantly more racism on campus, and are most vulnerable to underperformance because of stereotype threat. Mixed race blacks have the highest achievement rates relative to other blacks, typically remain on the fringes of the black student community, and perceive themselves to be categorically different than their same-race peers because of their mixed parentage.

So, as we would predict based on the color-SAT/ACT correlation, more mixed Blacks, adjudged from genealogy, outperform less mixed Blacks. This is in agreement with the ADD health, GSS, and NLY 97′ data.

The results remind me of a paper called “The superiority of the Mulatto” by E. B Reuter. Reuter lucidly discussed the Mulatto advantage phenomena circa 1919 and proposed cross-assortative mating as a partial explanation. That sounds like a much more plausible explanation than does one involving a stereotype threat that happens to affect Blacks in proportion to their African heritage, indexed either by color or genealogy. Mind you, the index of “vulnerable to underperformance because of stereotype threat” was the following question: “Next, For Each Group I Want To Know Whether You Think They Tend To Be Unintelligent Or Tend To Be Intelligent.” So the data implies that while less admixed Blacks are less intelligent — for whatever reason, of course — they have a good deal more common sense than their peers.

I would be interested in Charles et al.’s explanation for the color difference, which persists after factoring out mixed race individuals (at least in the other data sets). Perhaps Blacks of mixed parentage live a different life than their “multi-generational” peers and don’t see themselves as Black in the same way. So perhaps, they feel proportionately less threatened by stereotypes. But, for the rest, there is that “Skin color paradox”:

Dark-skinned blacks in the United States have lower socioeconomic status, more punitive relationships with the criminal justice system, diminished prestige, and less likelihood of holding elective office compared with their lighter counterparts. This phenomenon of “colorism” both occurs within the African American community and is expressed by outsiders, and most blacks are aware of it. Nevertheless, blacks’ perceptions of discrimination, belief that their fates are linked, or attachment to their race almost never vary by skin color. We identify this disparity between treatment and political attitudes as “the skin color paradox.” (Hochschild and Weaver, 2008. The Skin Color Paradox and the American Racial Order)

Since, in the Black population, one standard deviation of color is equivalent to approximately 1 point on a five point scale – refer to my previous discussion of the NLSF data — and IQ and color correlate at 0.15 in that population, the upper and lower end of the population (1s and 5s on a 5 point scale) differ by 0.6 SD, even though, according to Hochschild and Weaver (2008) they identify equivalently as Blacks. So, why do darker multi-generational Blacks perform less well than lighter multi-generational Blacks? (Presumably, it’s not because they have been reading my colorist commentary while reflecting on their reflectance.)

The Black intra-race difference is interesting because it resists environmental explanations even more than the Black-White inter race one does. While no one knows the heritability of IQ between racial populations, and therefore how much variance environmental factors explain, we do know the within race heritability. It’s high. If genes explain the lion’s share of cognitive variance within the Black population, it’s difficult to see how they don’t explain the lion’s share of variance between subpopulations defined by color or geology. The only way out is to argue that color is not correlated with IQ between kin (and therefore that heritability estimates can not be generalized across the Black color continuum). In the ADD health data, this explanation fails. None of this is a problem from environmentally inclined sociologists, of course, since they routinely fail to take into account the findings of behavioral genetics and psychometrics.

Whatever the case, I’ve identified yet another large sample that conforms to the predictions of a genetic hypothesis, both in terms of mixed race and color differences. (

Updated post

I updated my Blacks, IQ, and Color in the NLSF post. I goofed my original analysis. IQ is correlated with color about the same in this sample as in others. So if you’re worried about accusations of colorism going anywhere, worry not.

Is intra-Black “colorism” partially due to genetics?

In the last post I nihlistically concluded that: “The fact that there is a correlation, of course, does not reduce the environmental-genetic uncertainty much, as the correlation could always be explained environmentally.” I concluded this even after pointing to an analysis of the ADD health data by Guo and Stearns (2002) which found a wave I IQ heritability of .57 in the Black population. One might deduce that, were genes to explain 60% of the variance in the Black population, they should explain 60% of the variance between Black subpopulations defined by color. I dismissed this consideration, however, reasoning that environmentalists could always make their locality objection. Just as they vigorously maintain that one can not generalize within race h^2 estimates between races, they could maintain that one can not generalize these estimates between color groups within races. However, I just check the ADD health data. Apparently, the study was constructed to readily allow for behavior genetic analysis. Genetic kinships were oversampled and retained across the waves. The Black sample in wave III, in which color is recorded, contains enough full siblings, half siblings, MZ twins, DZ twins, and unrelated individuals to make a h^2 estimate for color, and if that index is found to be reliable enough, a within race between color continuum estimate of IQ h^2. This, of course, would be a relatively complex analysis — so I’m not going to attempt it myself. I spent the last couple of hour playing with the data and found that the IQ, color correlation did not vary significantly between related and unrelated individuals, which is suggestive. Anyways, if someone else is interested in working on this, let me know. Alternatively, you could sign up for one of this asshole’s courses:

“In my years as a white person co-facilitating anti-racism courses for primarily white audiences in a range of academic, corporate, and government institutions across the United States, Canada, and the United Kingdom, I have come to believe that the Discourse of Individualism is one of the primary barriers preventing well-meaning (and other) white people from understanding racism. …In my experience, when white people insist on Individualism in discussions about racism, they are in essence saying: My race has not made a difference in my life, so why do we have to talk about race as if it mattered?…Obviously I disagree with these familiar dominant claims, as they stand in the face of all evidence to the contrary, both research-based evidence of racial discrimination and disparity on every measure (see Copeland, 2005; Hochschild & Weaver, 2007; Micceri, 2009; Wessel, 2005) and visible evidence of ongoing patterns of segregation in education, economics, and housing.”(“Why Can’t We All Just Be Individuals?: Countering the Discourse of Individualism in Anti-racist Education”)

Blacks, IQ, and Color in the NLSF

[newer update: I guess I goofed with the original analysis. The data file was really difficult to handle and I had to compute a number of values. Somehow I didn’t properly exclude non-score SAT/ACT values (e.g. “enter 999 if you don’t know your score”). Anyways, I reran correlations after recomputing and found a -0.11 correlation between color (going from light to dark this time) and ACT/SAT in the total sample (n=766). When I excluded Blacks whose parents were not born in the US, the (weighted) correlation shot up to - 0.18 (n=552)

So using just the native sample, the n-weighted correlation summed across studies stands at 0.15 (N=4246).

[update:

JL, apt as ever, has proposed that the low correlation could be due to selection. Imagine if you selected Blacks and Whites for an IQ of 130. In that subpopulation, racial characteristics would, necessarily, be uncorrelated with IQ even though they are in the unselected population. Similarly, if you selected more and less admixed Blacks for an IQ of 130, racial admixture would, likewise, be uncorrelated (or less correlated) with IQ. Where there IQ differences and selection, one would, nonetheless, find something.. Namely, disproportionalities. As there would be proportionately fewer Blacks than Whites in the former case, in the latter there would be proportionately fewer less admixed Blacks than more admixed Blacks. This brings to mind that rather dated study, Witty and Jenkins (1936), that I once discussed.

To tests JL’s proposal, I compared The NLSF (native) Black sample and the ADDHealth Black national sample in terms of scores and two indices of admixture. To save myself some effort, I used Massey et al. (2007) as a reference for the NLSF data.

1. Nationally, Blacks (born of native parents) score about 850 on V+M SATs (SD= about 200). In the NLSF study, they scored, on average, 1193 circa 1998. So they were, in this sample, maybe 1.75 SD above the population mean. Being 1.75 SD above the national mean, we would expect the NLSF cohort to be at least 1.75 SD x 0.15 above the color mean if the IQ color correlation is around 0.15.

In the ADD health data, the mean color score was 2.34 (SD = 1.06) on a 1-5 scale running from black to white. In the NLSF, the mean score was 4.79 on a 0-10 scale running from white to black (In a figure, Massey et al. describes the scale as 1-10, but the “NATIONAL LONGITUDINAL SURVEY OF FRESHMEN PUBLIC RELEASE CODING MANUAL” indicates that it was a 0-10 scale.) Using the metrics of the Add Health data, Blacks in the NLSF have an equivalent color score of 2.85 or are 0.45 SD more light colored, which coheres with our expectation:

a. Convert the score from the 11 point scale to a score on a 10 point scale going from white to black ( 4.79 x (10/11) = 4.35)
b. Reverse scale to a black to white scale (10-=4.35 = 5.65) and reduce by ½ to a 5 point scale (5.65/2=2.825)
c. Convert to STDV (2.825-2.34)/1.06 =.45 SD)
d. Compare with expectation

3. Likewise with color, we would expect the NLSF cohort to be somewhat more admixed. Being 1.75 SD above the national mean, we would expect the NLSF cohort to be at least 1.75 SD x (some predicted IQ-ancestry correlation -- I've estimated this to be 0.25) above the national admixture mean, if the IQ white ancestry correlation was (some predicted IQ-ancestry correlation).

In the NLSF study, going by the data in Massey et alia, 16% of the native black group reported being mixed race (i.e. having one black and typically one white parent). In the ADD health data, according to Rowe (2002), out of a Black sample of 4271:

“127 adolescents were self-identified as inter-racial children because they had selected both the White and Black self-descriptors. Of these individuals, 102 were classified as Black by the interviewer. Parental reports were also used to identify possible inter-racial children. The head of household (usually the mother) reported her own race and that of her current spouse or partner. When one parent was reported as Black and the other as White and both lived in the household, the child was classified as interracial. Of 442 interracial children, 56 were classified by the interviewer as Black.”

This gives us a mixed race percent ranging from 3-10 percent. Using the midpoint as our estimate, the ratio of mixed to not is 0.07; and the ratio in the NLSF is .18. Which means that the NLSF cohort is .55 SD more admixed, which coheres with our expectation. (The NLSF cohort was born around 1981 and the inter-racial marriage rate was about 5% then, so this would likely be an underestimation of the NLSF mixed race overrepresentation – if that makes sense).

So, the data coheres with JL’s proposal.]

I suppose I should be commenting on the death of Kim Jong Il or something but…

I checked the test score – color correlation in the National Longitudinal Study of Freshman (NLSF). This was a fairly recent study of individuals at selective colleges. For self-identifying blacks with native born parents, the correlation between self reported SAT/ACT scores and interviewer assessed color was a very low = -0.034 (n= 658) (SATV= -.005; SATM= -.038; ACTC= -.069). This data point is questionable as self report has been found to be unreliable when it comes to scores, particularly when self-reporters have objectively assessed low scores. If we accept this data point, though, the n-weighted correlation stands at -0.13 (n= 4352). [REFER ABOVE.]

Blacks, IQ, and Color in the NLSY97

[note: JL has pointed out that subjective measures of skin color, as used in this data set, are much more unreliable than I initially conjectured. Apparently there's also a race by interviewer effect (Hill, 2002). Contrary to what some may conclude, this added unreliability means that the true associations between color and IQ is higher than found. In the same way, the unreliability of self-identified race as an index of true biogeographic-ancestry also means that the true association is higher -- i.e., the found correlations need to be corrected upward.]

Continuing with my most recent line of investigation, I looked at the association between skin color and aptitude tests in the NLSY97. You can read a description of that study here. It’s a follow up to the NLSY79 which, if you read the BC, you should be familiar with. The NLSY97 participants took a number of aptitude tests. Out of them, I selected the SAT verbal and qaunt, the Armed Services Vocational Aptitude Battery verbal and quant, and the Peabody Individual Achievement Test quant. The color-score correlation of 0.12 found for the ASVAB is close to the mean of all correlations. The correlations, again, are just those between color and scores within the self-identifying Black population. As I couldn’t find the relevant variables, I was unable to separate out immigrant Blacks from native Blacks; when I figure out how to do that — so as to follow up with a previous investigation, I will update this post. I didn’t feel like converting the ASVAB scores into IQ scores. For reference, the upper and lower 1/5th of the distribution differ by about 0.4 SD. (The scores are percentiles x 1000.)

Using the ASVAB scores as our index of IQ, this study puts the N-weighted correlation at 0.15 (N= 3694). (Ya, I actually look up those dusty old studies.)

Herskovits (1926)/r=0.17/n=115
Klineberg (1928)/r=0.12/n=139
Peterson and Lanier (1929)/r=0.18/n=83
Peterson and Lanier (1929)/r=0.3/n=75
Scarr et al. (1977)/r=0.155/n=288
Lynn (2002)/r=0.17/n=430
NLSY97 (unpublished)/r=0.12/1433
ADD Health (unpublished)/r=0.17/n=1131

And the average Cohen’s d between the upper and lower 4rths of the spectrum is about 0.5 n = >6,000 (Shuey’s pre-60′s data here)

Feguson (1919)/d= about 0.7/n=657
Feguson (1919)/d= about .9 SD/n=667
Kock and Simmons (1926)/d= about 0.15/n=1078
Klineberg (1928)/d= about 0.15/n=200
Young (1929)/ d= about 0.8 and 0.33/n=277
Peterson and Lanier (1929)/d = about 0.66/n=83
Peterson and Lanier (1929)/d= about 0.2 SD/m=83
Bruce (1940)/d=about 0.25/n=72
Codwell (1947)/d= about 0.33/n=480
Lynn (2002)/d= about 0.5/n=430
NLSY97 (unpublished)/d= about 0.4/n=1433
ADD Health (unpublished)/d=about 0.5/n=1131

It’s interesting that both the found correlations and mean differences show a good deal of cross temporal consistency.

I discussed what the predicted correlation for a genetic hypothesis would be elsewhere. It would be a function of a) the reliability of the measures of IQ and skin color (maybe 0.9 and ?), b) the correlation between color and African ancestry in the US Black population (about 0.45), c) and the correlation between IQ and White ancestry in the Black population, given the 1) restriction of range in the distribution of White ancestry in the Black population (? maybe 0.5), 2) the within population heritability of IQ (0.4 to 0.8, age depending), and 3) some proposed between population heritability (0.5 to 1). Contra Nisbett, for any hypothesis it would be below 0.20.

The fact that there is a correlation, of course, does not reduce the environmental-genetic uncertainty much, as the correlation could always be explained environmentally. Though, given that between family differences explain little variance in IQ, such explanations are constrained. (For example, Guo and Stearns (2002) found that between family effects explained only 17% of Black IQ variability in the ADD health data, data in which there was roughly a 1/2 SD difference between lighter and darker Black kids (ages ranging approximately from 12 to 18).) If not between family effects, then what? “Colorism” seems to be an obvious possibility — but it must work through some environmental mechanisms.

Whatever the case, from a Popperian perspective, a genetic hypothesis just survived another of my falsification attempts. As they say, that which does not falsify, makes stronger.

Color and IQ among African Americans in the ADD health data

I just ran partial correlations. The sample was filtered for self-indentifying US born African Americans (variable: H3OD4B) in wave III of the ADD health data. In the first table, “black” means “black color” and “white” means “white color.” The second table summarizes the within-between race differences. The thirds table lists the correlations. The correlations were significant in both Wave I and III of the study. Interestingly, the correlation increases with age, a phenomena which can be explained both environmentally and genetically.

Here’s eye color: