There were an endless debate about whether IQ heritability was spuriously inflated, while the growing evience, notably from modern techniques (e.g., GCTA), shows a non-negligible heritability in the narrow sense. A large part of the twin method estimates has been confirmed.
Il existe des débats persistants sur le fait que les estimations d’héritabilité de l’intelligence humaine serait trompeuses, qu’elles masquent des effets de corrélation gène-environnement (GxE). Heureusement, les techniques modernes permettent de tester la plausibilité de cette hypothèse. Une bonne partie des estimations d’héritabilité provenant de la méthode des jumeaux a pu être confirmée, la partie manquante s’expliquerait par la partie manquante de la variance génétique non capturée pour le moment par les techniques modernes. Les preuves d’effet additif de l’héritabilité, néanmoins, sont fortes.
I scanned “Educability and Group Differences” (Arthur Jensen, 1973). Here is the download link (124 MB). As always, if the link is not working, for any reason, send me an email at mh19870410 @ gmail . com. I can refresh the link whenever I want. A PDF version is now available here. Also, I selected some revealing passages of the book (see below).
A widely cited study (Eppig et al., 2010) suggested that infectious disease is the most important determinant of national IQs, independently and above GDP, education and some evolutionary variables. But their analysis is just a hierarchical multiple regression. It does not tell us anything about the arrow of causality. It is plausible that it goes both ways. Their results look like this :
The interesting fact is that they have used Lynn and Vanhanen’s (LVE) as well as Wicherts et al. (WEAM) IQ estimates. They demonstrate that the results are not significantly different for DALY disease and the evolutionary variables, which suggests that L&V estimates are not as inaccurate as is usually said.
Daniel A. Briley and Elliot M. Tucker-Drob (2013).
See supplemental materials.
Genes account for increasing proportions of variation in cognitive ability across development, but the mechanisms underlying these increases remain unclear. We conducted a meta-analysis of longitudinal behavioral genetic studies spanning infancy to adolescence. We identified relevant data from 16 articles with 11 unique samples containing a total of 11,500 twin and sibling pairs who were all reared together and measured at least twice between the ages of 6 months and 18 years. Longitudinal behavioral genetic models were used to estimate the extent to which early genetic influences on cognition were amplified over time and the extent to which innovative genetic influences arose with time. Results indicated that in early childhood, innovative genetic influences predominate but that innovation quickly diminishes, and amplified influences account for increasing heritability following age 8 years.
Angela M. Brant, Yuko Munakata, Dorret I. Boomsma, John C. DeFries, Claire M. A. Haworth, Matthew C. Keller, Nicholas G. Martin, Matthew McGue, Stephen A. Petrill, Robert Plomin, Sally J. Wadsworth, Margaret J. Wright, and John K. Hewitt. 2013.
IQ predicts many measures of life success, as well as trajectories of brain development. Prolonged cortical thickening observed in individuals with high IQ might reflect an extended period of synaptogenesis and high environmental sensitivity or plasticity. We tested this hypothesis by examining the timing of changes in the magnitude of genetic and environmental influences on IQ as a function of IQ score. We found that individuals with high IQ show high environmental influence on IQ into adolescence (resembling younger children), whereas individuals with low IQ show high heritability of IQ in adolescence (resembling adults), a pattern consistent with an extended sensitive period for intellectual development in more-intelligent individuals. The pattern held across a cross-sectional sample of almost 11,000 twin pairs and a longitudinal sample of twins, biological siblings, and adoptive siblings.
A. Alexander Beaujean (2005)
The purpose of this study is to meta-analyze the published studies that measure the performance differences in mental chronometric tasks using a behavioral genetic research design. Because chronometric tasks are so simple, individual differences in the time it takes to complete them are largely due to underlying biological and physiological mechanisms. The publications that come from these studies show trends, but they also show much heterogeneity, which makes it difficult to draw clear conclusions. Statistically integrating them through meta-analysis is a way to provide a clearer, more comprehensive picture of the magnitude of genetic influence involved in mental processing speed. Analyses from this study show that heritability is somewhat dependent on task difficulty, with performance on more complex tasks having a higher heritability than less difficult tasks. Implications of this study are twofold: (a) mental processing speed is partially heritable (h² estimates from .298 to .521); and (b) as chronometric task complexity increases, so does the heritability.
Studies of the nature of the Flynn Effect are usually done in developed countries (e.g., Rushton, 1999; Wicherts, 2004; Nijenhuis, 2007; for an ‘Overview of the Flynn Effect’, see Williams, 2013). There are two recent data on two developing countries (Khaleefa, 2009; Liu, 2012). The reported numbers on subtests gains can be studied using either MCV or PC analysis. Next, we will see that shared (c²) and non-shared (e²) environments, as measured by Falconer’s formula, are unrelated to heritability (h²) of the WAIS and WISC subtests. Culture load, heritability, g-loadings, and black-white differences tend to form a common cluster (on PC1) that is different from the pattern of loadings shown by shared and non-shared environment.
ARTHUR R. JENSEN and FRED W. JOHNSON
INTELLIGENCE 18, 309-333 (1994)
An analysis of IQ in relation to head size (and by inference, brain size) was performed on some 14,000 children and their full siblings, almost evenly divided by race (white and black) and sex, on whom data were obtained at ages 4 and 7 years in the National Collaborative Perinatal Project. Within each race X sex group, IQ is significantly correlated with head size, age and body size having been partialed out. A significant positive correlation between IQ X head size exists not only within subjects (at ages 4 and 7) but also within families and between families (at age 7 only). The within-families correlation (at age 7) is consistent with an intrinsic or pleiotropic correlation between the mental and physical variables. No significant positive correlation within families appeared at age 4, despite a significant within-subjects correlation at that age. As yet, there are only speculative explanations of the disparity between the age 4 and age 7 within-family correlations of head size with IQ. Although general body size is also correlated with IQ within subjects and between families, the correlation does not exist within families in either age group, which rules out a pleiotropic correlation between body size and IQ. There are both race and sex differences in head size, although the sex difference in IQ is nil. White and black children who are matched on IQ show, on average, virtually zero difference in head size.