The nature of the black–white difference on various psychometric tests: Spearman's hypothesis

Response to Difficulty Drives Variation in IQ Test Performance

In a large (N = 300), pre-registered experiment and data analysis model, we find that individual variation in overall performance on Raven's Progressive Matrices is substantially driven by differential strategizing in the face of difficulty. Some participants choose to spend more time on hard problems while others choose to spend less and these differences explain about 42% of the variance in overall performance. In a data analysis jointly predicting participants' reaction times and accuracy on each item, we find that the Raven's task captures at most half of participants' variation in time-controlled ability (48%) down to almost none (3%), depending on which notion of ability is assumed. Our results highlight the role that confounding factors such as motivation play in explaining individuals' differential performance in IQ testing.

Between-Group Mean Differences in Intelligence in the United States Are >0% Genetically Caused: Five Converging Lines of Evidence

The past 30 years of research in intelligence has produced a wealth of knowledge about the causes and consequences of differences in intelligence between individuals, and today mainstream opinion is that individual differences in intelligence are caused by both genetic and environmental influences. Much more contentious is the discussion over the cause of mean intelligence differences between racial or ethnic groups. In contrast to the general consensus that interindividual differences are both genetic and environmental in origin, some claim that mean intelligence differences between racial groups are completely environmental in origin, whereas others postulate a mix of genetic and environmental causes. In this article I discuss 5 lines of research that provide evidence that mean differences in intelligence between racial and ethnic groups are partially genetic. These lines of evidence are findings in support of Spearman’s hypothesis, consistent results from tests of measurement invariance across American racial groups, the mathematical relationship that exists for between-group and within-group sources of heritability, genomic data derived from genome-wide association studies of intelligence and polygenic scores applied to diverse samples, and admixture studies. I also discuss future potential lines of evidence regarding the causes of average group differences across racial groups. However, the data are not fully conclusive, and the exact degree to which genes influence intergroup mean differences in intelligence is not known. This discussion applies only to native English speakers born in the United States and not necessarily to any other human populations.

The Hare and the Hedgehog: Empirical evidence on the relationship between the individual Pace of Life and the speed-accuracy continuum

Against the background of the speed-accuracy trade-off, we explored whether the Pace of Life can be used to identify heterogeneity in the strategy to place more weight on either fast or accurate accomplishments. The Pace of Life approaches an individual's exposure to time and is an intensively studied concept in the evolutionary biology research. Albeit overall rarely, it is increasingly used to understand human behavior and may fulfill many criteria of a personal trait. In a controlled laboratory environment, we measured the participants' Pace of Life, as well as their performance on a real-effort task. In the real-effort task, the participants had to encode words, whereby each word encoded correctly was associated with a monetary reward. We found that individuals with a faster Pace of Life accomplished more tasks in total. At the same time, they were less accurate and made more mistakes (in absolute terms) than those with a slower Pace of Life. Thus, the Pace of Life seems to be useful to identify an individual's stance on the speed-accuracy continuum. In our specific task, placing more weight on speed instead of accuracy paid off: Individuals with a faster Pace of Life were ultimately more successful (with regard to their monetary revenue).

Are cognitive differences between immigrant and majority groups diminishing?

A review is given of scores on various cognitive measures, comparing groups of ethnic Dutch and non‐Western immigrants using a large number of datasets.

The research shows that there are large group differences in school results, work proficiency, and g for Turks, Moroccans, Surinamese, Netherlands Antilleans, and Indonesians from the Moluccans compared with ethnic Dutch. However, South‐East Asians score higher, and persons with one immigrant and one ethnic Dutch parent score only slightly below the mean of the Dutch. When comparing first‐generation disadvantaged immigrant groups with later generations the data show substantial improvements for g, a remarkable stability of educational differences for younger children, and a clear improvement in educational achievement at the end of primary school. Indirect data on intergenerational improvements in work proficiency appear suggestive of a trend of closing gaps.

Some of the data reflect higher cognitive capacities over time, and this enhances integration of immigrants into Dutch society. Causes of group differences and improvements in mean level of g are discussed. Copyright © 2004 John Wiley & Sons, Ltd.

Linking ecology and cognition: does ecological specialisation predict cognitive test performance?

Variation in cognitive abilities is thought to be linked to variation in brain size, which varies across species with either social factors (Social Intelligence Hypothesis) or ecological challenges (Ecological Intelligence Hypothesis). However, the nature of the ecological processes invoked by the Ecological Intelligence Hypothesis, like adaptations to certain habitat characteristics or dietary requirements, remains relatively poorly known. Here, we review comparative studies that experimentally investigated interspecific variation in cognitive performance in relation to a species’ degree of ecological specialisation. Overall, the relevant literature was biased towards studies of mammals and birds as well as studies focusing on ecological challenges related to diet. We separated ecological challenges into those related to searching for food, accessing a food item and memorising food locations. We found interspecific variation in cognitive performance that can be explained by adaptations to different foraging styles. Species-specific adaptations to certain ecological conditions, like food patch distribution, characteristics of food items or seasonality also broadly predicted variation in cognitive abilities. A species’ innovative problem-solving and spatial processing ability, for example, could be explained by its use of specific foraging techniques or search strategies, respectively. Further, habitat generalists were more likely to outperform habitat specialists. Hence, we found evidence that ecological adaptations and cognitive performance are linked and that the classification concept of ecological specialisation can explain variation in cognitive performance only with regard to habitat, but not dietary specialisation.

Global Ancestry and Cognitive Ability

Using data from the Philadelphia Neurodevelopmental Cohort, we examined whether European ancestry predicted cognitive ability over and above both parental socioeconomic status (SES) and measures of eye, hair, and skin color. First, using multi-group confirmatory factor analysis, we verified that strict factorial invariance held between self-identified African and European-Americans. The differences between these groups, which were equivalent to 14.72 IQ points, were primarily (75.59%) due to difference in general cognitive ability (g), consistent with Spearman’s hypothesis. We found a relationship between European admixture and g. This relationship existed in samples of (a) self-identified monoracial African-Americans (B = 0.78, n = 2,179), (b) monoracial African and biracial African-European-Americans, with controls added for self-identified biracial status (B = 0.85, n = 2407), and (c) combined European, African-European, and African-American participants, with controls for self-identified race/ethnicity (B = 0.75, N = 7,273). Controlling for parental SES modestly attenuated these relationships whereas controlling for measures of skin, hair, and eye color did not. Next, we validated four sets of polygenic scores for educational attainment (eduPGS). MTAG, the multi-trait analysis of genome-wide association study (GWAS) eduPGS (based on 8442 overlapping variants) predicted g in both the monoracial African-American (r = 0.111, n = 2179, p < 0.001), and the European-American (r = 0.227, n = 4914, p < 0.001) subsamples. We also found large race differences for the means of eduPGS (d = 1.89). Using the ancestry-adjusted association between MTAG eduPGS and g from the monoracial African-American sample as an estimate of the transracially unbiased validity of eduPGS (B = 0.124), the results suggest that as much as 20%–25% of the race difference in g can be naïvely explained by known cognitive ability-related variants. Moreover, path analysis showed that the eduPGS substantially mediated associations between cognitive ability and European ancestry in the African-American sample. Subtest differences, together with the effects of both ancestry and eduPGS, had near-identity with subtest g-loadings. This finding confirmed a Jensen effect acting on ancestry-related differences. Finally, we confirmed measurement invariance along the full range of European ancestry in the combined sample using local structural equation modeling. Results converge on genetics as a potential partial explanation for group mean differences in intelligence.

Filling in the Gaps: The Association between Intelligence and Both Color and Parent-Reported Ancestry in the National Longitudinal Survey of Youth 1997

Little research has dealt with intragroup ancestry-related differences in intelligence in Black and White Americans. To help fill this gap, we examined the association between intelligence and both color and parent-reported ancestry using the NLSY97. We used a nationally-representative sample, a multidimensional measure of cognitive ability, and a sibling design. We found that African ancestry was negatively correlated with general mental ability scores among Whites (r = −0.038, N = 3603; corrected for attenuation, rc = −0.245). In contrast, the correlation between ability and parent-reported European ancestry was positive among Blacks (r = 0.137, N = 1788; rc = 0.344). Among Blacks, the correlation with darker skin color, an index of African ancestry, was negative (r = −0.112, N = 1455). These results remained with conspicuous controls. Among Blacks, both color and parent-reported European ancestry had independent effects on general cognitive ability (color: β = −0.104; ancestry: β = 0.118; N = 1445). These associations were more pronounced on g-loaded subtests, indicating a Jensen Effect for both color and ancestry (rs = 0.679 to 0.850). When we decomposed the color results for the African ancestry sample between and within families, we found an association between families, between singletons (β = −0.153; N = 814), and between full sibling pairs (β = −0.176; N = 225). However, we found no association between full siblings (β = 0.027; N = 225). Differential regression to the mean results indicated that the factors causing the mean group difference acted across the cognitive spectrum, with high-scoring African Americans no less affected than low-scoring ones. We tested for measurement invariance and found that strict factorial invariance was tenable. We then found that the weak version of Spearman’s hypothesis was tenable while the strong and contra versions were not. The results imply that the observed cognitive differences are primarily due to differences in g and that the Black-White mean difference is attributable to the same factors that cause differences within both groups. Further examination revealed comparable intraclass correlations and absolute differences for Black and White full siblings. This implied that the non-shared environmental variance components were similar in magnitude for both Blacks and Whites.

Spearman's hypothesis tested comparing Korean young adults with various other groups of young adults on the items of the Advanced Progressive Matrices

Spearman's hypothesis tested at the subtest level of an IQ battery states that differences between races on the subtests of an IQ battery are a function of the g loadings of these subtests, such that there are small differences between races on subtests with low g loadings and large differences between races on subtests with high g loadings. Jensen (1998) stated that Spearman's hypothesis is a law-like phenomenon. It has also been confirmed many times at the level of items of the Raven's Progressive Matrices. This study hypothesizes that with concern to Spearman's hypothesis, subtests and items function in fundamentally the same way, and tested whether Spearman's hypothesis is confirmed at the item level for White-East Asian comparisons. A group of Korean young adults (N=205) was compared with other groups of young adults from Canada, the US, Russia, Peru and South Africa (total N=4770) who took the Advanced Progressive Matrices. Spearman's hypothesis was strongly confirmed with a sample-size-weighted r with a value of 0.63. Computing the g loadings of the items of the Raven with either the Raven-g or the Wechsler-g led to the same conclusions. Tests of Spearman's hypothesis yielded less-strong outcomes when the 36-item Advanced Progressive Matrices were used than when the 60-item Standard Progressive Matrices were used. There is a substantial correlation between sample size and the outcome of Spearman's hypothesis. So, all four hypotheses were confirmed, showing that a part of the subtest-level nomological net replicates at the item level, strengthening the position that, with concern to Spearman's hypothesis, subtests and items function fundamentally the same. It is concluded that Spearman's hypothesis is still a law-like phenomenon. Detailed suggestions for follow-up research are made.

A Meta-Analysis of Spearman’s Hypothesis Tested on Latin-American Hispanics, Including a New Way to Correct for Imperfectly Measuring the Construct of g

Spearman’s hypothesis states that the difference in intelligence between groups is a function of the g loadings of the subtests, where larger differences are found on tests with higher g loadings. This finding has consistently been supported on various groups. In this study we look at samples of Latin-American Hispanics in comparison to Whites. We carried out a meta-analysis based on 14 data points and a total of 16,813 Latin-American Hispanics, including a new way to correct for imperfectly measuring the construct of g. Spearman’s hypothesis was strongly supported with a mean r of 0.63. After correction for various statistical artifacts this value became rho = 0.91. Therefore, we conclude that Spearman’s hypothesis also holds true for White/Latin-American Hispanic differences.

A Meta-Analysis of Spearman’s Hypothesis Tested on Latin-American Hispanics, Including a New Way to Correct for Imperfectly Measuring the Construct of g

Spearman’s hypothesis states that the difference in intelligence between groups is a function of the g loadings of the subtests, where larger differences are found on tests with higher g loadings. This finding has consistently been supported on various groups. In this study we look at samples of Latin-American Hispanics in comparison to Whites. We carried out a meta-analysis based on 14 data points and a total of 16,813 Latin-American Hispanics, including a new way to correct for imperfectly measuring the construct of g. Spearman’s hypothesis was strongly supported with a mean r of 0.63. After correction for various statistical artifacts this value became rho = 0.91. Therefore, we conclude that Spearman’s hypothesis also holds true for White/Latin-American Hispanic differences.

Spearman’s Hypothesis Tested Comparing 47 Regions of Japan Using a Sample of 18 Million Children

Many groups differ in their mean intelligence score. Spearman’s hypothesis states that the differences are a function of cognitive complexity. There tend to be large differences on subtests of high cognitive complexity and small differences on subtests of low cognitive complexity. Spearman’s hypothesis has been supported by a large number of studies. Can Spearman’s hypothesis be generalized to regions of a country, where these regions differ in mean intelligence? We utilized data from 86 different cognitive tests from all 47 Japanese prefectures and correlated the g loadings of 86 subtests with standardized differences on the same subtests. Spearman’s hypothesis was clearly supported: the biggest differences between the regions were on the tests that were of the greatest complexity, meaning that Spearman’s hypothesis may be generalizable from groups to regions. In Japan, g loadings offer a better explanation of group differences in intelligence than cultural differences. Future research should explore whether Spearman’s hypothesis is also supported for differences between regions of other countries.

Spearman’s Hypothesis Tested Comparing 47 Regions of Japan Using a Sample of 18 Million Children

Many groups differ in their mean intelligence score. Spearman’s hypothesis states that the differences are a function of cognitive complexity. There tend to be large differences on subtests of high cognitive complexity and small differences on subtests of low cognitive complexity. Spearman’s hypothesis has been supported by a large number of studies. Can Spearman’s hypothesis be generalized to regions of a country, where these regions differ in mean intelligence? We utilized data from 86 different cognitive tests from all 47 Japanese prefectures and correlated the g loadings of 86 subtests with standardized differences on the same subtests. Spearman’s hypothesis was clearly supported: the biggest differences between the regions were on the tests that were of the greatest complexity, meaning that Spearman’s hypothesis may be generalizable from groups to regions. In Japan, g loadings offer a better explanation of group differences in intelligence than cultural differences. Future research should explore whether Spearman’s hypothesis is also supported for differences between regions of other countries.

Relationship between Rate of Preparation for, and Processing of, an Event Requiring a Choice Response

It is known that alcohol increases the time taken to identify signals and to make responses to them, but it is not known whether it also slows the rate of preparation for such events. These two performance parameters are not necessarily related, as age affects the former but not the latter. Twenty subjects participated in a 4-choice reaction time experiment in which they received no alcohol (NA) in the first session and either no alcohol (10 subjects) or 0.8 ml alcohol (A) per kg body weight (10 subjects) in the second session. In each session there were 300 practice trials, followed by 400 experimental trials at each one of five Response–Stimulus Intervals (RSI: 50, 100, 200, 400, and 800 msec). There was a significant effect of alcohol such that the reduction in response time from the first to the second session was 39 msec larger for the NA/NA group than for the NA/A group. Response time decreased significantly with increasing RSI, but there was no interaction between the effect of alcohol and RSI. Thus, alcohol slows the processing of an event requiring a choice response; however, like age and individual differences, but unlike practice, alcohol has no effect on the rate of preparation for that event. In addition, an analysis of what happened before and after an error revealed that practice and increasing RSI produce real improvements in performance rather than shifts in the tradeoff between speed and accuracy, whereas alcohol produces a real impairment. It is concluded that the relationship between the rate of preparation for, and processing of, a stimulus is not simple, as one factor (practice) influences both rates, whereas other factors (alcohol, individual differences, and age) influence the rate of processing only.

General Mental Ability

Individual differences on diverse tests of mental abilities that range in complexity from simple reaction time to abstract reasoning are all positively correlated in the population. The total covariance among all such tests can be analyzed into a number of uncorrelated components of variance, or factors, that, in terms of their generality, are hierarchical, with the most general factor, or g, at the apex. This g factor is common to every type of cognitive performance, whatever other ability factors may be involved (e.g., verbal, spatial, numerical, musical, etc.), and is the crucial factor in most tests' practical validity. Its correlations with various tests' heritability, inbreeding depression, heterosis, average evoked potentials, brain metabolism, and many other physical correlates indicate that as a product of evolution it is profoundly enmeshed with many organismic variables. A theory based on empirical evidence links g to neural processes involved in the speed and efficiency of information processing.

Ethnic Group, Education, and Gender Differences on Six Horn Abilities for Adolescents and Adults

This study examined test performance by a sample of 1,146 individuals (587 males, 559 females) aged 15 to 93 years on six abilities derived from Horn's Gf-Gc theory. Differences related to gender, ethnic group (White, Black, Hispanic), and educational attainment were explored by means of multivariate and univariate analyses. The following Horn abilities were evaluated, in most cases by a single reliable subtest: Fluid (Gf), Crystallized (Gc), Broad Visualization (Gv), Quantitative (Gq), Short-Term Acquisition and Retrieval (SAR) and Long-Term Retrieval (TSR). Data were analyzed for 956 Whites, 128 Blacks, and 62 Hispanics; gender and ethnic group differences were evaluated both with and without an education covariate. Educational attainment, ethnic group, and gender produced significant main effects in the MANOVA, and the latter two variables remained significant in the MANCOVA with education covaried. Whites scored significantly higher than Blacks on all Horn abilities, with and without the covariation. In the White-Hispanic comparisons, most significant differences dropped out with education covaried. Correlations between education and test performance were higher for males than females.

Explaining Cross-Cultural Differences

Contrary to the tradition in cross-cultural psychology in which bias is identified with the stimulus by culture interaction in an analysis of variance design, it is argued (and illustrated) here that any main effect or interaction term in such a design can reflect bias. It is suggested that difficulties in the interpretation of observed cross-cultural differences in data can be avoided only if the researcher succeeds in introducing external variables in terms of which the variance in the factor culture can be reduced to zero. This implies, somewhat paradoxically, that in a satisfactory cross-cultural study there is no variance left to be explained in terms of culture.

Racial Identity and Career Assessment

In the career assessment literature, relatively little attention is given to the matter of the influence of racial factors on assessees' responses to traditional assessment measures. In this paper, I argue that racial identity models could provide a framework by which to investigate the influence of racial factors on the career decision- making process but existing measures are inadequate for this purpose. The construct of racial salience is used to discuss hypothesized deficiencies in the career maturity and congruence racial group comparison assessment literature, and to recommend ways in which measures could be modified to incorporate race- related theory more directly.

Race and General Cognitive Ability: The Myth of Diminishing Returns to Education

The impact of education on racial differences in general cognitive ability was assessed using data from the National Longitudinal Survey of Youth. To control for attrition during the educational process, we compared the scores of individuals who ultimately attained the same level of education but who were tested at different points in their educational careers. Multiple regression analyses revealed that education can have a strong positive effect on cognitive ability in both whites and blacks. Whites benefited more from education than blacks during the high school years, but blacks benefited much more than whites from a college education, substantially narrowing the gap between the races. These findings contradict the hypothesis that racial differences in intelligence are relatively immutable, in part because of the diminishing returns from increases in education.

Intelligence 2.0: Reestablishing a Research Program on g in I–O Psychology

Intelligence (i.e., g, general mental ability) is an individual difference that is arguably more important than ever for success in the constantly changing, ever more complex world of business (Boal, 2004; Gatewood, Field, & Barrick, 2011). Although the field of industrial–organizational (I–O) psychology initially made substantial contributions to the study of intelligence and its use in applied settings (e.g., Hunter, 1980; Schmidt & Hunter, 1981), we have done relatively little in recent times about studying the nature of the intelligence construct and its measurement. Instead, we have focused predominately on using intelligence to predict performance outcomes and examine racial subgroup differences on intelligence test scores. Although the field of I–O psychology continues to approach intelligence at a surface level, other fields (e.g., clinical psychology, developmental and educational research, and neuropsychology) have continued to study this construct with greater depth and have consequently made more substantial progress in understanding this critical and complex construct. The purpose of this article is to note this lack of progress in I–O psychology and to challenge our field to mount new research initiatives on this critical construct.

A measurement perspective on affirmative action in U.S. medical education

BACKGROUND

The U.S. Supreme Court has recently heard another affirmative action case, and similar programs to promote equitable representation in higher education are being debated and enacted around the world. Understanding the empirical and quantitative research conducted over the last 50 years is important in designing effective and fair initiatives related to affirmative action in medical education. Unfortunately, the quantitative measurement research relevant to affirmative action is poorly documented in the scholarly journals that serve medical education.

METHODS

This research organizes and documents the measurement literature relevant to enacting affirmative action within the medical school environment, and should be valuable for informing future actions. It provides summaries of those areas where the research evidence is strong and highlights areas where more research evidence is needed. To structure the presentation, 10 topic areas are identified in the form of research questions.

RESULTS

Measurement evidence related to these questions is reviewed and summarized to provide evidence-based answers.

CONCLUSIONS

These answers should provide a useful foundation for making important decisions regarding the use of racial diversity initiatives in medical education.

Why IQ is not a covariate in cognitive studies of neurodevelopmental disorders

IQ scores are volatile indices of global functional outcome, the final common path of an individual's genes, biology, cognition, education, and experiences. In studying neurocognitive outcomes in children with neurodevelopmental disorders, it is commonly assumed that IQ can and should be partialed out of statistical relations or used as a covariate for specific measures of cognitive outcome. We propose that it is misguided and generally unjustified to attempt to control for IQ differences by matching procedures or, more commonly, by using IQ scores as covariates. We offer logical, statistical, and methodological arguments, with examples from three neurodevelopmental disorders (spina bifida meningomyelocele, learning disabilities, and attention deficit hyperactivity disorder) that: (1) a historical reification of general intelligence, g, as a causal construct that measures aptitude and potential rather than achievement and performance has fostered the idea that IQ has special status and that in studying neurocognitive function in neurodevelopmental disorders; (2) IQ does not meet the requirements for a covariate; and (3) using IQ as a matching variable or covariate has produced overcorrected, anomalous, and counterintuitive findings about neurocognitive function.

Brain Wave Concomitants of Cross-Cultural Differences in Scores On Simple Cognitive Tasks

Interpretations of cross-cultural differences in performance on cognitive tasks tend to rely on broad concepts, such as general intelligence or cultural modes of thinking. In this study, the authors examine two proximate parameters, stimulus complexity and task exposure, using reaction time (RT) and event-related brain potentials (ERPs) recorded during various tasks. Five tasks differed in complexity but had similar stimulus content; one task had stimuli of different appearance. Test trials were administered across three days. Participants were trained on most tasks for two days. There were three samples, rural Venda youngsters in South Africa with little schooling, Venda university students, and Dutch university students. Cross-cultural differences in RT increased with task complexity and decreased with exposure. Substantial correspondence was found between patterns of RT and latency of the N2, an ERP component related to stimulus categorization. Our results fit an explanation in terms of task familiarity. Implications for culture-cognition relationships are discussed.