Personality, intelligence and proof-reading

Two studies sought to determine personality and cognitive ability correlates of proof-reading. In both studies candidates were given 5 min to identify up to 55 errors in a 920 word, two page document. In Study 1, which tested 240 school children, fluid intelligence (as measured by the Baddeley Reasoning Test) was the highest correlate of proof-reading (r = .30). Eleven percent of the variance in total attempted scores was accounted for by intelligence, Introversion and low Conscientiousness. In the second study 70 undergraduates completed the same proof-reading test along with two intelligence tests (Baddeley Reasoning Test; Wonderlic Personnel Test) and a more robust personality measure (NEO-FFI). Proof-reading was correlated with both intelligence tests (Baddeley r = .45; Wonderlic r = .40). More of the variance was accounted for in the total attempted-score of errors than for a correct errors-detected score. When the two intelligence and five personality trait scores were regressed on to the proof-reading test score over a quarter of the variance (Adj R² = .28) was accounted for, but only the Baddeley test was a significant predictor (Beta = .39).     

Clocking g: Relating intelligence and measures of timed performance

The relationships between intelligence test scores and measures derived from reaction time (RT) and perceptual speed procedures were investigated in 137 twelve-year-old students with IQs ranging from 59 to 142. A range of intelligence tests were used and the scores factor analyzed to produce general, spatial and verbal factors. Test and factor scores were correlated with perceptual speed and with measures taken from 2, 4, and 8 choice RT tasks using a response keyboard upon which the subject's fingers directly rested, thus avoiding interpretive problems associated with a “home key.” Inspection time correlated poorly with intelligence. Only three of the RT measures produced correlations greater than .25 with the general factor. These were the slope of Hick's law, B, (correlation −.28), the 8 choice mean RT, RT8, (−.33) and the 8 choice standard deviation, SD8 (−.41), compared with the average intercorrelation between the intelligence measures of .40. Test-retest correlations of the RT measures, taken over a year for half the subjects, were low as reliability measures, with .35 for B, .52 for RT8, and .48 for SD8. Correlations of RT measures with spatial scores were not significantly greater than with verbal scores, suggesting that whatever relationship exists is with a general factor rather than only a spatial one.     

Associations between cortical thickness and general intelligence in children,adolescents and young adults

Neuroimaging research indicates that human intellectual ability is related to brain structure including the thickness of the cerebral cortex. Most studies indicate that general intelligence is positively associated with cortical thickness in areas of association cortex distributed throughout both brain hemispheres. In this study, we performed a cortical thickness mapping analysis on data from 182 healthy typically developing males and females ages 9 to 24 years to identify correlates of general intelligence (g) scores. To determine if these correlates also mediate associations of specific cognitive abilities with cortical thickness, we regressed specific cognitive test scores on g scores and analyzed the residuals with respect to cortical thickness. The effect of age on the association between cortical thickness and intelligence was examined. We found a widely distributed pattern of positive associations between cortical thickness and g scores, as derived from the first unrotated principal factor of a factor analysis of Wechsler Abbreviated Scale of Intelligence (WASI) subtest scores. After WASI specific cognitive subtest scores were regressed on g factor scores, the residual score variances did not correlate significantly with cortical thickness in the full sample with age covaried. When participants were grouped at the age median, significant positive associations of cortical thickness were obtained in the older group for g-residualized scores on Block Design (a measure of visual-motor integrative processing) while significant negative associations of cortical thickness were observed in the younger group for g-residualized Vocabulary scores. These results regarding correlates of general intelligence are concordant with the existing literature, while the findings from younger versus older subgroups have implications for future research on brain structural correlates of specific cognitive abilities, as well as the cognitive domain specificity of behavioral performance correlates of normative gray matter thinning during adolescence.     

Ability EI as an intelligence? Associations of the MSCEIT with performance on emotion processing and social tasks and with cognitive ability

Associations among the MSCEIT, a broad-bandwidth measure of ability emotional intelligence (EI), self-report EI, social perception ability, psychometric intelligence and performance on inspection time (IT) tasks, which assessed the speed of processing of emotional and non-emotional information were investigated in two student samples (N=99, 199). The main findings were that MSCEIT scores were unrelated to fluid ability or speed of non-emotional information processing as assessed by IT, but evidence for associations of MSCEIT scores with crystallised ability was found. Positive associations were found between MSCEIT scores, self-report EI and some emotion/social task scores. The results suggest that EI as assessed by the MSCEIT has some properties of an intelligence and is more closely related to crystallised than to fluid ability. The relatively small MSCEIT/g _c correlations suggest that the MSCEIT is not a pure ability measure, although restriction of range in the samples used may also be relevant. More work, and the development of new measures, is required to determine whether performance EI has a fluid component.     

Reaction time correlations with intelligence test scores obtained under either timed or untimed conditions

One hundred and thirteen high school students were randomly assigned to one of two groups that were administered an intelligence test (the Multidimensional Aptitude Battery) under either timed or untimed conditions. Subsequently, all subjects were given a battery of 8 reaction time tests. Multiple regression analyses showed that combinations of RTs were approximately equally good predictors of IQ scores in both groups. Zero-order correlations between each RT test and IQ scores were also approximately equal for timed and untimed Verbal and Full-Scale scores but correlations with Performance scores were higher in the timed condition. The extent to which the different RT tests correlated with timed scores was quite highly related to the tests' loadings on a general speed factor but these loadings were not related to the tests' correlations with untimed scores. Rather, the relative complexity of the RT tests had a stronger influence on their correlations with IQ scores in the untimed condition. It is concluded that timed and untimed intelligence tests impose different information-processing demands on subjects but that the speed with which subjects can cope with these demands is equally important in both conditions.     

Is the Flynn effect on g?: A meta-analysis

Black/White differences in mean IQ have been clearly shown to strongly correlate with g loadings, so large group differences on subtests of high cognitive complexity and small group differences on subtests of low cognitive complexity. IQ scores have been increasing over the last half century, a phenomenon known as the Flynn effect. Flynn effect gains are predominantly driven by environmental factors. Might these factors also be responsible for group differences in intelligence? The empirical studies on whether the pattern of Flynn effect gains is the same as the pattern of group differences yield conflicting findings. A psychometric meta-analysis on all studies with seven or more subtests reporting correlations between g loadings and standardized score gains was carried out, based on 5 papers, yielding 11 data points (total N = 16,663). It yielded a true correlation of − .38, and none of the variance between the studies could be attributed to moderators. It appears that the Flynn effect and group differences have different causes. Suggestions for future research are discussed.     

An integrated perspective on the relation between response speed and intelligence

Research in the field of mental chronometry and individual differences has revealed several robust regularities (Jensen, 2006). These include right-skewed response time (RT) distributions, the worst performance rule, correlations with general intelligence (g) that are more pronounced for RT standard deviations (RTSD) than they are for RT means (RTm), an almost perfect linear relation between individual differences in RTSD and RTm, linear Brinley plots, and stronger correlations between g and inspection time (IT) than between g and RTm. Here we show how all these regularities are manifestations of a single underlying relationship, when viewed through the lens of Ratcliff’s diffusion model ( [Ratcliff, 1978] and [Ratcliff et al., 2008] ). The single underlying relationship is between individual differences in general intelligence and individual differences in “drift rate”, which is just the speed of information processing in Ratcliff’s model. We also test and confirm a strong prediction of the diffusion model, namely that the worst performance rule generalizes to phenomena outside of the field of intelligence. Our approach provides an integrative perspective on intelligence findings.     

The relationship between speed of information processing and cognitive ability

Speed of information processing as measured by various reaction time and inspection tasks has been shown to correlate with psychometric intelligence, and it has been suggested that general intelligence (g) is determined to some degree by the speed that information is processed. If this is so, then various measures of speed of information processing should correlate substantially with each other, and each should also correlate with a wide range of psychometric tests that load on g. Alternatively, intelligence may be considered to be a multi-faceted complex of partially related abilities with specific abilities being dependent upon specific cognitive processes. If this is the case, it should be possible to discover independent cognitive processes, some of which correlate with one facet or broad ability and some with another. This paper presents three experiments in which the relationship between intellectual ability and four speed of information processing measures was examined. These were rate of memory scanning, rate of retrieval of information from long term memory, speed of stimulus-response mapping and inspection time (IT). Results showed that correlations between IT and most reaction time measures of speed of information processing were low, and that correlations between different versions of IT were negligible. In addition, some cognitive tasks with verbal material (memory scanning rate for digits and Posner letter matching IT) correlated most substantially with Verbal Reasoning whereas non-verbal (two-line) IT consistently correlated with tests loading on g. It was thus suggested that while non-verbal IT may be a measure of a perceptual speed attribute that contributes to mental functioning, other “speed of information processing” parameters may be more specific to a subset of abilities.     

An exploration of genetic g: Hierarchical factor analysis of cognitive data from the western reserve twin project

Hierarchical factor analyses involving Schmid-Leiman transformations (Schmid & Leiman, 1957) were conducted on specific cognitive abilities data collected in a sample of 148 identical (MZ) and 135 same-sex fraternal (DZ) twin pairs. Two main questions were addressed: First, are genetic influences on specific cognitive abilities simply a reflection of their g loading, or are different sets of genes affecting separate abilities? Second, to the extent that specific cognitive abilities are affected by common genetic variance, how similar is the common genetic factor to a phenotypic factor reflecting g? Model fitting results suggest that genetic influences on specific abilities are a reflection of both general intelligence and genetic influences specific to separate abilities and that loadings on the common genetic factor are more highly correlated with phenotypic g loadings than are common environmental factor loadings.     

Gray matter and intelligence factors: Is there a neuro-g?

Heterogeneous results among neuro-imaging studies using psychometric intelligence measures may result from the variety of tests used. The g-factor may provide a common metric across studies. Here we derived a g-factor from a battery of eight cognitive tests completed by 6929 young adults, 40 of whom also completed structural MRI scans. Regional gray matter (GM) was determined using voxel-based-morphometry (VBM) and correlated to g-scores. Results showed correlations distributed throughout the brain, but there was limited overlap with brain areas identified in a similar study that used a different battery of tests to derive g-scores. Comparable spatial scores (with g variance removed) also were derived from both batteries, and there was considerable overlap in brain areas where GM was correlated to the respective spatial scores. The results indicate that g-scores derived from different test batteries do not necessarily have equivalent neuro-anatomical substrates, suggesting that identifying a “neuro-g” will be difficult. The neuro-anatomical substrate of a spatial factor, however, appears more consistent and implicates a distributed network of brain areas that may be involved with spatial ability. Future imaging studies directed at identifying the neural basis of intelligence may benefit from using a psychometric test battery chosen with specific criteria.     

Humphreys's attenuated test of Spearman's hypothesis

Humphreys's test of Spearman's hypothesis (viz., that the size of the standardized black-white differences on various psychometric tests is positively related to the tests' loadings on g, the general intelligence factor) is methodologically weak. It is based on comparison of a fairly representative sample of the black population of U.S. school children with a highly selected sample of the white school population, representing the lowest 15 to 20% of whites in socio-economic status (SES). A fair test of the hypothesis requires that the black and white samples should not be selected on any g-correlated variable, such as SES. Selection attenuates and distorts the relationship between tests' g loadings and the magnitude of the standardized mean black-white differences on the tests. Other unorthodox conditions in Humphreys's study, such as performing factor analysis on the test-score means of various arbitrary demographic groups instead of on individual test scores inflates tests' g loadings and biases the test of Spearman's hypothesis by restriction of reliable variance in g loadings. Humphreys's study cannot be considered a proper replication of Jensen's examination of Spearman's hypothesis in 11 different studies comprising 74 different tests, which consistently bears out Spearman's hypothesis.     

Factor Analytic Modeling of Within Person Variation in Score Profiles

A profile is a vector of scores for one examinee. The mean score in the vector can be interpreted as a measure of overall profile height, the variance can be interpreted as a measure of within person variation, and the ipsatized vector of score deviations about the mean can be said to describe the pattern in the score profile. A within person pattern interpretation of orthogonal factor loadings is developed. A statistic is proposed to index the amount of within person variation accounted for by an orthogonal factor. The statistic can be used to determine whether a factor warrants a within person pattern interpretation. A factor model with a random coefficient intercept is proposed for the study of within person score patterns accounting for within person variation. Two examples, one involving items from the Life Orientation Test and the other involving subscales of the Strong Vocational Interest Inventory, illustrate application of the factor model with an intercept, the within person variation statistic, and the profile pattern interpretation of factor loadings. With empirical support from the examples, it is conjectured that theoretically important traits often manifest themselves through within person score patterns.     

An Evaluation of Spearman's Hypothesis by Manipulating g Saturation

Spearman's Hypothesis holds that the magnitude of mean White–Black differences on cognitive tests covaries with the extent to which a test is saturated with g. This paper evaluates Spearman's Hypothesis by manipulating the g saturation of cognitive composites. Using a sample of 16,384 people from the General Aptitude Test Battery database, we show that one can decrease mean racial differences in a g test by altering the g saturation of the measure. Consistent with Spearman's Hypothesis, the g saturation of a test is positively and strongly related to the magnitude of White–Black mean racial differences in test scores. We demonstrate that the reduction in mean racial differences accomplished by reducing the g saturation in a measure is obtained at the cost of lower validity and increased prediction errors. We recommend that g tests varying in mean racial differences be examined to determine if the Spearman's Hypothesis is a viable explanation for the results.     

The Validity of the SHL Customer Service Questionnaire (CSQ)

This study set out to validate the Saville and Holdsworth (SHL) Customer Services Questionnaire (CSQ) by relating test scores to ‘objective measures’ like absenteeism, punctuality, and letters of compliment and complaint, as well as subjective supervisor rating measures. Over 170 airport staff served as subjects. The dependent measures were logically related one to another and there were a few sex and rank differences on them. A number of significant correlations between CSQ subscales and the dependent measures showed two subscales (TC4) Approach to Organizing and (EC2) Need for Results the best correlates of the dependent variable. Of the subscales scores within the three factor scores Relations with People showed fewest significant correlations, and Emotions and Energy most. Results were discussed in terms of the limited research in this field.     

The Sternberg Triarchic Abilities Test (STAT) as a measure of academic achievement and general intelligence

The degree to which practical, creative, and analytical abilities, measured by the Sternberg Triarchic Abilities Test (STAT) (Sternberg, 1993), significantly contribute to the prediction of academic achievement, independent of general intelligence, was investigated. Although Sternberg et al. (2000) claim that the STAT is not related to, nor a measure of, general intelligence, data obtained by Sternberg, Ferrari, Clinkenbeard, and Grigorenko (1996), found that STAT scores were significantly correlated with measures of general intelligence. In the present study, introductory psychology midterm examination grades, STAT scores, and Wonderlic Personnel Test scores (as a measure of general intelligence), were obtained from undergraduate students at the University of Western Ontario (N=150). Total STAT scores and each of the STAT subsection scores were significantly related to Wonderlic test scores, P<0.01, and the STAT subsections were significantly related to each other, P<0.01. The partial correlations between midterm grades and creative, practical, analytical, and total STAT scores, with the variance due to the Wonderlic test removed, were also found to be significant for practical and for total STAT scores, P<0.05, but nonsignificant for creative and analytical STAT scores. A factor analysis including midterm examination grades, the Wonderlic test, and each of the STAT subsections revealed a single general factor. Thus, some results supported Sternberg but others were contrary to his claims.     

Personality and intelligence as predictors of creativity

Participants completed the Big Five NEO-FFI (Costa & McCrae, 1992) as a personality measure, the Wonderlic Personnel Test (Wonderlic, 1992) as an intelligence measure, and four measures of creativity: Guilford’s (1967) unusual uses divergent thinking test; the Biographical Inventory of Creative Behaviours; a self-rated measure of creativity; and the Barron–Welsh Art Scale to measure creative judgement. Extraversion was significantly related to all four measures of creativity. Intelligence failed to add any incremental variance in predicting the creativity scores. Multiple regression indicated that up to 47% of the variance in divergent thinking scores can be accounted for by the Big Five personality traits. Personality correlates to creativity vary as a function of the creativity measure.     

Personality,intelligence and proof-reading

Two studies sought to determine personality and cognitive ability correlates of proof-reading. In both studies candidates were given 5 min to identify up to 55 errors in a 920 word, two page document. In Study 1, which tested 240 school children, fluid intelligence (as measured by the Baddeley Reasoning Test) was the highest correlate of proof-reading (r = .30). Eleven percent of the variance in total attempted scores was accounted for by intelligence, Introversion and low Conscientiousness. In the second study 70 undergraduates completed the same proof-reading test along with two intelligence tests (Baddeley Reasoning Test; Wonderlic Personnel Test) and a more robust personality measure (NEO-FFI). Proof-reading was correlated with both intelligence tests (Baddeley r = .45; Wonderlic r = .40). More of the variance was accounted for in the total attempted-score of errors than for a correct errors-detected score. When the two intelligence and five personality trait scores were regressed on to the proof-reading test score over a quarter of the variance (Adj R² = .28) was accounted for, but only the Baddeley test was a significant predictor (Beta = .39).     

A review of the worst performance rule: Evidence, theory, and alternative hypotheses

This paper reviews evidence, theory, and alternative hypotheses for the worst performance rule (WPR), which states that on multitrial cognitive tasks, worst performance trials predict general intelligence (g) better than best performance trials. A review of the relevant evidence indicates that the WPR has been found for a variety of participants, tasks, and measures. A review of relevant theories reveals that the WPR appears to be related to cognitive factors (e.g., lapses in working memory) as well as biological factors (e.g., individual differences in neural oscillations). A review of alternative hypotheses shows that the WPR cannot be attributed to statistical or data artifacts such as outliers, unreliable measurement, or variance compression. The preponderance of evidence supports the hypothesis that the WPR holds for cognitive tasks high in g saturation but not for cognitive tasks low in g saturation. The paper ends with a call for research on the causes of the WPR and for research on the correlates of best performance.     

Group differences and first principal-component loadings in the Hawaii family study of cognition: a test of the generality of ‘Spearman's hypothesis’

The generality of Spearman's hypothesis that varying differences between whites and blacks on various tests of mental ability are correlated with their g-loadings was tested by analyzing group data from the Hawaii Family Study of Cognition. Data from the three largest ethnic groups tested in the Hawaii Study (Americans of Japanese, Chinese or European ancestry; total N = 5333) were subjected to a principal-component analysis and the first principal component was used as a measure of g. Ethnic group and generation (parent-offspring) differences on 15 tests of specific cognitive abilities were then correlated with their first principal-component loadings. In general, correlations between ethnic group differences and g-loadings are smaller than those recently reported for white-black differences by Jensen (1983); however, those between generation differences and g-loadings are larger. Ethnic group differences on first principal-component scores in the Hawaii Study are less than parent-offspring differences; thus, the correlation between group differences on tests of mental ability and their g-loadings may be a function of the magnitude of the group difference for general mental ability. Because a group difference on g requires group differences on tests which load on g, an observed group difference in general mental ability may necessarily result in a correlation between group differences on individual tests and their g-loadings.     

Sex differences in brain volume are related to specific skills, not to general intelligence

It has been proposed that males would show higher mean scores than females in general intelligence (g) because (1) men have, on average, larger brains than women, and (2) brain volume correlates with g. Here we report a failure to support the conclusion derived from these premises. High resolution MRIs were acquired in a sample of one hundred healthy young participants for estimating total, gray, and white matter volumes. Participants also completed an intelligence battery - comprising tests measuring abstract, verbal, and spatial abilities - that allowed the extraction of g scores. Results showed consistent relations between sex differences in brain volumes and non-g spatial and verbal skills but not for g.