Large Cross-National Differences in Gene × Socioeconomic Status Interaction on Intelligence

In the paper

“In order to ensure that effect sizes were placed on a metric that was comparable across studies, we ensured that phenotypes and continuous SES measures were Z-transformed (based on the M and SD from data pooled across all twins and siblings of all relatedness types) prior to fitting the Purcell (2002) model.”

What the sources say

• Supported

  The citation identifies the model the citing authors fitted, not the source of their Z-transformation procedure. The paper’s “Continuous Moderator Variables” section describes a gene–environment interaction model with continuous moderators, including socioeconomic status. The sentence presents standardization for cross-study comparability as the citing authors’ own choice. (LLM, conf=0.91)

  cites Purcell (2002) source

In the paper

“findings generally supported by heritability estimates from genome-wide data on unrelated individuals (Davies et al., 2011; Plomin et al., 2013).”

What the sources say

• Partly supported

  The Abstract and Discussion report genome-wide estimates from unrelated adults that support substantial heritability of intelligence. The paper does not show that heritability increases; its estimates concern fluid and crystallized intelligence in middle to older adulthood, not a change over time. (LLM, conf=0.84)

  cites Davies et al., 2011 sourceExperimental — accuracy not yet measured
• Partly supported

  The Discussion reports a substantial GCTA estimate for general cognitive ability, and the Genomewide Complex-Trait Analysis section reports estimates from unrelated adults and children. The paper describes increasing heritability from childhood to adulthood as a finding from developmental research, but does not show that genome-wide estimates establish that increase. (LLM, conf=0.86)

  cites Plomin et al., 2013 sourceExperimental — accuracy not yet measured

In the paper

“and increase with age (Briley & Tucker-Drob, 2013)”

What the sources say

• Supported

  The Results section reports that this longitudinal meta-analysis largely confirmed developmental increases in heritability, with larger increases associated with older ages. The Abstract identifies the underlying data as twin and sibling pairs measured repeatedly from infancy through adolescence. (LLM, conf=0.92)

  cites Briley & Tucker-Drob, 2013 source

In the paper

“there was significant support for age differences in the a and c parameters, indicating that genetic variance increases and shared environmental variance decreases with age”

What the sources say

• Partly supported

  The Results section (Changes in genetic and environmental factors; page not provided) reports significant longitudinal increases in heritability and decreases in shared environmentality. But these are changes in proportions of variance: the Discussion (Strengths and limitations; page not provided) says the study could not adequately assess changes in absolute genetic or environmental variance. The claim's unqualified statement about variance therefore exceeds the findings. (LLM, conf=0.87)

  cites Briley & Tucker-Drob, 2013 sourceExperimental — accuracy not yet measured
• Partly supported

  The Abstract reports significant age-related increases in heritability and a decline in shared environmental influence for the broader 11,000-pair sample, citing an earlier analysis. But this paper’s Results (Heterogeneity model-fitting analyses; page unavailable) found no significant age-group differences in A, C, or E for its high-cognitive-ability sample. The claim does not distinguish the earlier finding from this paper’s own result. (LLM, conf=0.84)

  cites Haworth et al., 2009 sourceExperimental — accuracy not yet measured

In the paper

“Other studies, however, have failed to replicate the finding (Bartels, van Beijsterveldt, & Boomsma, 2009; Kremen et al., 2005; Soden-Hensler, 2012; van der Sluis, Willemsen, de Geus, Boomsma, & Posthuma, 2008), including the largest sample to date (Hanscombe et al., 2012).”

What the sources say

• Supported

  The Results report no obvious differences in twin correlations across maternal-education levels. The Discussion reports only a small genetic-influence difference between the low- and middle-education groups, with the estimate higher in the low-education group; this supports citing Bartels et al. as a failure to replicate the G × SES pattern. The separate claim about the largest sample is attributed to Hanscombe et al., not Bartels et al. (LLM, conf=0.87)

  cites Bartels, van Beijsterveldt, & Boomsma, 2009 source
• Supported

  The Discussion (p. 12) reports no increase in genetic variance with parental education and concludes that the study found a parental-education × shared-environment interaction only, not a parental-education × gene interaction. The 'largest sample to date' clause is attributed to Hanscombe et al. (2012), not to Kremen et al. (LLM, conf=0.90)

  cites Kremen et al., 2005 source
• Partly supported

  The Discussion reports that this large UK-representative study did not replicate the predicted genetic interaction between SES and children's IQ. The Methods (Participants) report 8,716 twin pairs, but the passages in our copy do not establish that it was the largest sample to date. (LLM, conf=0.82)

  cites Hanscombe et al., 2012 sourceExperimental — accuracy not yet measured

In the paper

“Indeed, both phenomena may reflect a process of increased and accumulated effects of gene-environment transactions with the increased opportunity that comes with both social class and age (Tucker-Drob et al., 2013; Turkheimer & Horn, 2014).”

What the sources say

• Supported

  The Abstract says transactional processes can produce increasing genetic influence with both age and environmental opportunity. The Socioeconomic Differences in Heritability section links opportunity to SES and notes that positive Gene × SES findings have mostly come from the United States. The claim appropriately presents this shared mechanism as a possibility, not an established cause. (LLM, conf=0.93)

  cites Tucker-Drob et al., 2013 source
• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Turkheimer & Horn, 2014

In the paper

“There is also some indication that the shared and non-shared environmental variance components decrease with SES, although these interactions were not statistically significant.”

In the paper

“but no G × SES effect for non-US studies (a′ = −.001, SE = .033, p = .979).”

In the paper

“None of these moderators achieved statistical significance.”

In the paper

“In conclusion, all robustness checks indicated the presence of a significantly positive G × SES interaction in the US but not in Western Europe/Australia, with the difference between US and non-US studies being statistically significant.”

In the paper

“our meta-analytic dataset consisted of k = 43 effect sizes from a total of N = 24,926 pairs of twins and siblings (approximately 50,000 individuals) participating in K = 14 independent studies.”

In the paper

“Data were relatively evenly split across US (k = 18, K = 8, N = 10,831) and Non-US (Western Europe and Australia) samples (k = 25, K = 6, N = 14,095).”

In the paper

“and a significant difference between US and non-US studies (difference = .135, SE = .042, p = .001).”

In the paper

“When only US studies were entered into p-curve analysis, p-checker indicated that the p-curve is, in fact, right skewed, indicating that these studies contain evidential value (z = −3.427, p < .001).”

In the paper

“We did not find evidence of publication or reporting bias in our meta-analytic dataset. Both visual and formal tests of funnel plot asymmetry were not significant, both when applied to the overall meta-analytic dataset, and when separately applied to effects sizes from US and non-US samples.”

In the paper

“Genes account for considerably more variation in intelligence at both higher ages and in higher US socioeconomic contexts.”

In the paper

“Consistent with the cross national difference identified in our primary meta-analysis, p-curve analysis further indicated evidential value for a non-zero G × SES effect in US studies, but did not indicate evidential value for a nonzero G × SES effect in the non-US studies.”

In the paper

“Second, in studies conducted outside the US (in Western Europe and Australia), the best estimate for G × SES magnitude was very slightly negative, and not significantly different from zero.”

In the paper

“We included multiple effect sizes per sample (e.g. for different intelligence measures, different waves, or different measures of SES), weighted meta-regression models by the reciprocal number of effect sizes included for the corresponding sample and by the inverse of each parameter’s sampling variance, and implemented a sandwich estimator that corrects standard errors for non-independence of data”

In the paper

“Additionally, Harden et al. (2007) reported evidence for G × SES interaction in a positively selected sample of US adolescents that contained very few racial minorities.”

What the sources say

• ?Not matched

  Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  cites Harden et al. (2007)

In the paper

“We used sophisticated methods for estimating random effects meta-regressions in nested data (i.e., in a meta-analytic dataset that contained multiple effect sizes per study).”

• Also stated in: § Meta-Analyzing Effect Sizes · plain

  “Random effects models do not require the traditional assumption that all effect sizes were derived from the same population with a single true effect size. Rather, they allow for population variation in the true effect size above and beyond variation attributable to sampling error.”

In the paper

“Because this methodology required that all effect sizes and standard errors be calculated using a consistent modeling approach, we typically (a) obtained the raw data and re-analyzed it ourselves, (b) were provided with parameter estimates from re-analyses by the original study authors (all authors contacted complied with our request), or (c) re-analyzed the published sub-group covariance matrices”

In the paper

“we meta-analyzed tests of G × SES interaction on intelligence and academic achievement test scores, allowing for stratification by nation (US vs non-US), and conducted rigorous tests for publication bias and between-study heterogeneity.”

In the paper

“The results indicate that G × SES effects are not uniform, but can rather take positive, zero, and even negative values depending on factors that differ at the national-level.”