Search Results

Source: Intelligence
Resulting in 46 citations.
1. Ang, Siew Ching
Rodgers, Joseph Lee
Wänström, Linda
The Flynn Effect Within Subgroups in the U.S.: Gender, Race, Income, Education, and Urbanization Differences in the NLSY-Children Data
Intelligence 38,4 (July-August 2010): 367-384.
Also: http://www.sciencedirect.com/science/article/pii/S0160289610000504
Cohort(s): Children of the NLSY79
Publisher: Elsevier
Keyword(s): Digit Span (also see Memory for Digit Span - WISC); Ethnic Studies; Flynn Effect; Gender; Household Income; I.Q.; Mothers, Education; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Racial Studies; Urbanization/Urban Living

Although the Flynn Effect has been studied widely across cultural, geographic, and intellectual domains, and many explanatory theories have been proposed, little past research attention has been paid to subgroup differences. Rodgers and Wanstrom (2007) identified an aggregate-level Flynn Effect (FE) at each age between 5 and 13 in the Children of the National Longitudinal Survey of Youth (NLSYC) PIAT-Math data. FE patterns were not obtained for Reading Recognition, Reading Comprehension, or Digit Span, consistent with past FE research suggesting a closer relationship to fluid intelligence measures of problem solving and analytic reasoning than to crystallized measures of verbal comprehension and memory. These prior findings suggest that the NLSYC data can be used as a natural laboratory to study more subtle FE patterns within various demographic subgroups. We test for subgroup Flynn Effect differences by gender, race/ethnicity, maternal education, household income, and urbanization. No subgroups differences emerged for three demographic categories. However, children with more educated (especially college educated) mothers and/or children born into higher income households had an accelerated Flynn Effect in their PIAT-M scores compared to cohort peers with lower educated mothers or lower income households. We interpret both the positive and the null findings in relation to previous theoretical explanations. [Copyright Elsevier]
Bibliography Citation
Ang, Siew Ching, Joseph Lee Rodgers and Linda Wänström. "The Flynn Effect Within Subgroups in the U.S.: Gender, Race, Income, Education, and Urbanization Differences in the NLSY-Children Data." Intelligence 38,4 (July-August 2010): 367-384.
2. Beaujean, A. Alexander
Osterlind, Steven J.
Using Item Response Theory to Assess the Flynn Effect in the National Longitudinal Study of Youth 79 Children and Young Adults Data
Intelligence 36,5 (September-October 2008): 455-463.
Also: http://www.sciencedirect.com/science/article/pii/S0160289607001304
Cohort(s): Children of the NLSY79
Publisher: Elsevier
Keyword(s): Flynn Effect; I.Q.; Intelligence Tests; Peabody Individual Achievement Test (PIAT- Math); Peabody Picture Vocabulary Test (PPVT); Test Scores/Test theory/IRT

The purpose of this manuscript is to assess the magnitude of the Flynn Effect (i.e., increase in mean IQ scores across time) using Item Response Theory (IRT). Unlike using methods derived from Classical Test Theory, IRT has the capability to determine if the Flynn Effect is due to a genuine increase in intelligence, if it is due to a psychometric artifact (i.e., items changing properties over time), or a combination of the two. Using the Peabody Picture Vocabulary Test—Revised and Peabody Individual Achievement Test—Math from the National Longitudinal Study of Youth 79 Children and Young Adults, the results of this study indicate that while using raw and standardized scores, the Flynn Effect is evident in a predicted magnitude, but when using scores based from IRT analysis, the magnitude Flynn Effect substantially decreases, and, at least for the Peabody Picture Vocabulary Test—Revised, goes away. Thus, for the data used in this study, the Flynn Effect appears to be largely the result of changing item properties instead of changes in cognitive ability.
Bibliography Citation
Beaujean, A. Alexander and Steven J. Osterlind. "Using Item Response Theory to Assess the Flynn Effect in the National Longitudinal Study of Youth 79 Children and Young Adults Data." Intelligence 36,5 (September-October 2008): 455-463.
3. Boutwell, Brian B.
Connolly, Eric J.
Barbaro, Nicole
Shackelford, Todd K.
Petkovsek, Melissa
Beaver, Kevin M.
On the Genetic and Environmental Reasons Why Intelligence Correlates with Criminal Victimization
Intelligence 62 (May 2017): 155-166.
Also: http://www.sciencedirect.com/science/article/pii/S0160289617300077
Cohort(s): NLSY79 Young Adult, NLSY97
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Bullying/Victimization; Family Influences; Intelligence; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Siblings

Researchers have expended considerable effort to understand the causes and correlates of criminal victimization. More recently, scholars have focused on identifying individual-level traits that increase the odds of victimization. Generally absent from this line of research, however, is examining the extent to which previously unmeasured genetic and environmental influences contribute to the covariation between victimization and individual-level risk factors. The current study aims to replicate and extend prior research by examining the contribution of genetic and environmental influences on the association between intelligence and victimization by analyzing twin and sibling data from two nationally representative samples of American youth. Quantitative genetic analyses indicate that common additive genetic factors, as well as non-shared environmental factors, explained the phenotypic association between intelligence and victimization. Finally, our results revealed that after correcting for possible familial confounding, the effect of intelligence on victimization experiences remained statistically significant. The findings of the current study replicate and extend prior research on the phenotypic association between indicators of general intelligence and the experience of victimization.
Bibliography Citation
Boutwell, Brian B., Eric J. Connolly, Nicole Barbaro, Todd K. Shackelford, Melissa Petkovsek and Kevin M. Beaver. "On the Genetic and Environmental Reasons Why Intelligence Correlates with Criminal Victimization." Intelligence 62 (May 2017): 155-166.
4. Cleveland, Hobart Harrington
Jacobson, Kristen C.
Lipinski, John J.
Rowe, David C.
Genetic and Shared Environmental Contributions to the Relationship between the Home Environment and Child and Adolescent Achievement
Intelligence 28,1 (February 2000): 69-86.
Also: http://www.sciencedirect.com/science/article/pii/S016028969900029X
Cohort(s): Children of the NLSY79
Publisher: Elsevier
Keyword(s): Genetics; Home Observation for Measurement of Environment (HOME); Modeling; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Peabody Picture Vocabulary Test (PPVT); Siblings

The present study used prospective data to examine the relationship between the family environment (as measured by the Home Observation for Measurement of the Environment-Short Form [HOME-SF]) and child and adolescent achievement, and to determine the genetic and environmental contributions to this relationship. Data are from 2108 full- and half-sibling pairs from the National Longitudinal Survey of Youth Child data set (NLSY-Child). The average age of participants was 11.9 for older siblings (SD = 3.0) and 8.2 for younger siblings (SD = 2.8). The structural equation modeling program, Mx, was used to obtain the most precise estimates of genetic and environmental contributions to variation in the HOME-SF, variation in achievement, and to the covariation between the HOME-SF and achievement. According to the best-fitting, most parsimonious model, common genetic factors explained approximately one-quarter of the correlation between the HOME-SF and achievement, whereas common shared environmental factors explained the majority (75%) of this relationship. Genetic influences also accounted for over one-third of the variation in both the HOME-SF and achievement. Shared environmental influences explained 35% and 50% of the variation in achievement and the HOME-SF, respectively. The discussion mentions possible mechanisms by which genetic and environmental factors exert their influence on the relationship between the HOME-SF and achievement.
Bibliography Citation
Cleveland, Hobart Harrington, Kristen C. Jacobson, John J. Lipinski and David C. Rowe. "Genetic and Shared Environmental Contributions to the Relationship between the Home Environment and Child and Adolescent Achievement." Intelligence 28,1 (February 2000): 69-86.
5. Coyle, Thomas R.
Ability Tilt for Whites and Blacks: Support for Differentiation and Investment Theories
Intelligence 56 (May-June 2016): 28-34.
Also: http://www.sciencedirect.com/science/article/pii/S0160289616300447
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Aptitude; Armed Services Vocational Aptitude Battery (ASVAB); College Major/Field of Study/Courses; Racial Differences; STEM (Science, Technology, Engineering & Mathematics); Test Scores/Test theory/IRT

This research is the first to examine race differences in ability tilt for whites and blacks, two groups that show an average difference in g (favoring whites) of about one standard deviation. Tilt was defined as within-subject differences in math and verbal scores on three aptitude tests (SAT, ACT, PSAT). These differences yielded math tilt (math > verbal) and verbal tilt (verbal > math), which were correlated with specific abilities (verbal and math) and college majors in STEM (science, technology, engineering, math) and the humanities. Math tilt was higher for whites than blacks, whereas verbal tilt was similar for both groups. In addition, tilt correlated positively with similar majors and abilities (e.g., math tilt and math ability), and negatively with competing majors and abilities (e.g., math tilt and verbal ability). Tilt effects were generally stronger for whites, and were unrelated to g. The results support differentiation theories, which predict higher levels of tilt for higher ability subjects, and investment theories, which predict negative tilt effects for competing abilities (e.g., math tilt and verbal ability).
Bibliography Citation
Coyle, Thomas R. "Ability Tilt for Whites and Blacks: Support for Differentiation and Investment Theories." Intelligence 56 (May-June 2016): 28-34.
6. Coyle, Thomas R.
Non-g Residuals of Group Factors Predict Ability Tilt, College Majors, and Jobs: A Non-g Nexus
Intelligence 67 (March-April 2018): 19-25.
Also: https://www.sciencedirect.com/science/article/pii/S0160289617302349
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Armed Services Vocational Aptitude Battery (ASVAB); Cognitive Ability; College Major/Field of Study/Courses; Occupations; STEM (Science, Technology, Engineering & Mathematics); Test Scores/Test theory/IRT

This study examined the predictive power of non-g residuals of group factors (based on multiple tests) for diverse criteria (e.g., aptitude tests, college majors, occupations). Test scores were drawn from the National Longitudinal Survey of Youth (N = 1950). Four group factors (math, verbal, speed, shop/technical) were estimated using the Armed Services Vocational Aptitude Battery, a diverse battery of 12 cognitive tests. The residuals of the group factors were estimated after removing g (variance common to all tests) and were correlated with aptitude test scores (SAT, ACT, PSAT), ability tilt (i.e., difference between math and verbal scores on the aptitude tests), and college majors and jobs in science, technology, engineering, and math (STEM) and the humanities. The math residuals correlated positively with math/STEM criteria and negatively with verbal/humanities criteria. In contrast, the verbal residuals showed the opposite pattern. The residuals of the two non-academic factors (speed and shop) generally correlated negligibly with all criteria. The results are the first to demonstrate the predictive power of group factor residuals for diverse criteria. The findings extend prior research on non-g factors for individual tests (SAT and ACT) and provide evidence of a non-g nexus involving group factors. The pattern of results supports investment theories, which predict that investment in one area (math) correlates positively with complementary criteria (math/STEM) but negatively with competing criteria (verbal/humanities).
Bibliography Citation
Coyle, Thomas R. "Non-g Residuals of Group Factors Predict Ability Tilt, College Majors, and Jobs: A Non-g Nexus." Intelligence 67 (March-April 2018): 19-25.
7. Coyle, Thomas R.
Relations among General Intelligence (g), Aptitude Tests, and GPA: Linear Effects Dominate
Intelligence 53 (November-December 2015): 16-22.
Also: http://www.sciencedirect.com/science/article/pii/S0160289615001051
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Armed Services Vocational Aptitude Battery (ASVAB); Grade Point Average (GPA)/Grades; Intelligence; Test Scores/Test theory/IRT

This research examined linear and nonlinear (quadratic) relations among general intelligence (g), aptitude tests (SAT, ACT, PSAT), and college GPAs. Test scores and GPAs were obtained from the National Longitudinal Survey of Youth (N = 1950) and the College Board Validity Study (N = 160670). Regressions estimated linear and quadratic relations among g, based on the Armed Services Vocational Aptitude Battery, composite and subtest scores of aptitude tests, and college GPAs. Linear effects explained almost all the variance in relations among variables. In contrast, quadratic effects explained trivial additional variance among variables (less than 1%, on average). The results do not support theories of intelligence (threshold theories or Spearman's Law of Diminishing Returns), which predict that test scores lose predictive power with increases in ability level or at a certain threshold.
Bibliography Citation
Coyle, Thomas R. "Relations among General Intelligence (g), Aptitude Tests, and GPA: Linear Effects Dominate." Intelligence 53 (November-December 2015): 16-22.
8. Coyle, Thomas R.
Tech Tilt Predicts Jobs, College Majors, and Specific Abilities: Support for Investment Theories
Intelligence 75 (July-August 2019): 33-40.
Also: https://www.sciencedirect.com/science/article/pii/S0160289618302587
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Armed Services Vocational Aptitude Battery (ASVAB); Cognitive Ability; College Major/Field of Study/Courses; STEM (Science, Technology, Engineering & Mathematics); Test Scores/Test theory/IRT

Specific cognitive abilities include ability tilt, based on within-subject differences in math and verbal scores on standardized tests (e.g., SAT, ACT). Ability tilt yields math tilt (math > verbal), which predicts STEM (science, technology, engineering, math) criteria, and verbal tilt (verbal > math), which predicts humanities criteria. The current study examined a new type of tilt: tech tilt, based on within-subject differences in technical scores and academic scores (math or verbal) on the Armed Services Vocational Aptitude Battery. (Technical scores tapped vocational skills for electronics, mechanics, cars, and tools.)
Bibliography Citation
Coyle, Thomas R. "Tech Tilt Predicts Jobs, College Majors, and Specific Abilities: Support for Investment Theories." Intelligence 75 (July-August 2019): 33-40.
9. Coyle, Thomas R.
Pillow, David R.
SAT and ACT Predict College GPA After Removing g
Intelligence 36,6 (November-December 2008): 719-729.
Also: http://www.sciencedirect.com/science/article/pii/S0160289608000603
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Armed Services Vocational Aptitude Battery (ASVAB); g Factor; I.Q.; Intelligence; Modeling, Structural Equation; Test Scores/Test theory/IRT; Tests and Testing

This research examined whether the SAT and ACT would predict college grade point average (GPA) after removing g from the tests. SAT and ACT scores and freshman GPAs were obtained from a university sample (N = 161) and the 1997 National Longitudinal Study of Youth (N = 8984). Structural equation modeling was used to examine relationships among g, GPA, and the SAT and ACT. The g factor was estimated from commercial cognitive tests (e.g., Wonderlic and Wechsler Adult Intelligence Scale) and the computer-adaptive Armed Services Vocational Aptitude Battery. The unique variances of the SAT and ACT, obtained after removing g, were used to predict GPA. Results from both samples converged: While the SAT and ACT were highly g loaded, both tests generally predicted GPA after removing g. These results suggest that the SAT and ACT are strongly related to g, which is related to IQ and intelligence tests. They also suggest that the SAT and ACT predict GPA from non-g factors. Further research is needed to identify the non-g factors that contribute to the predictive validity of the SAT and ACT.
Bibliography Citation
Coyle, Thomas R. and David R. Pillow. "SAT and ACT Predict College GPA After Removing g." Intelligence 36,6 (November-December 2008): 719-729.
10. Coyle, Thomas R.
Purcell, Jason M.
Snyder, Anissa
Kochunov, Peter
Non-g Residuals of the SAT and ACT Predict Specific Abilities
Intelligence 41,2 (March-April 2013): 114-120.
Also: http://www.sciencedirect.com/science/article/pii/S0160289612001444#sec2.1
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Armed Services Vocational Aptitude Battery (ASVAB); Cognitive Ability; g Factor; Test Scores/Test theory/IRT; Tests and Testing

This research examined whether non-g residuals of the SAT and ACT subtests, obtained after removing g, predicted specific abilities. Non-g residuals of the verbal and math subtests of the SAT and ACT were correlated with academic (verbal and math) and non-academic abilities (speed and shop), both based on the Armed Services Vocational Aptitude Battery. Non-g residuals of the SAT and ACT math subtests were positively related to math ability and negatively to verbal ability, whereas the opposite pattern was found for the verbal subtests. Non-g residuals of both sets of subtests were weakly related to non-academic abilities. The results support an investment theory of skills and abilities: Investing in skills in one area (e.g., math) improves abilities in that area but lowers abilities in competing areas (e.g., verbal).
Bibliography Citation
Coyle, Thomas R., Jason M. Purcell, Anissa Snyder and Peter Kochunov. "Non-g Residuals of the SAT and ACT Predict Specific Abilities." Intelligence 41,2 (March-April 2013): 114-120.
11. Coyle, Thomas R.
Purcell, Jason M.
Snyder, Anissa
Richmond, Miranda C.
Ability Tilt on the SAT and ACT Predicts Specific Abilities and College Majors
Intelligence 46 (September-October 2014): 18-24.
Also: http://www.sciencedirect.com/science/article/pii/S016028961400049X
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Cognitive Ability; College Major/Field of Study/Courses; Test Scores/Test theory/IRT

This research examined the validity of ability tilt, measured as within-subject differences in math and verbal scores on the SAT and ACT. Tilt scores were correlated with academic abilities (math and verbal) and college majors (STEM and humanities), both drawn from the National Longitudinal Survey of Youth. Math tilt (math > verbal) correlated positively with math ability and negatively with verbal ability, whereas verbal tilt (verbal > math) showed the opposite pattern. In addition, math tilt was associated with STEM majors (e.g., science and math), whereas verbal tilt was associated with humanities majors (e.g., English and history). Both math and verbal tilt were unrelated to non-academic abilities (speed and shop) and g. The results support niche-picking and investment theories, in which investment in one area (math) means less investment in competing areas (verbal).
Bibliography Citation
Coyle, Thomas R., Jason M. Purcell, Anissa Snyder and Miranda C. Richmond. "Ability Tilt on the SAT and ACT Predicts Specific Abilities and College Majors." Intelligence 46 (September-October 2014): 18-24.
12. Coyle, Thomas R.
Snyder, Anissa
Richmond, Miranda C.
Sex Differences in Ability Tilt: Support for Investment Theory
Intelligence 50 (May-June 2015): 209-220.
Also: http://www.sciencedirect.com/science/article/pii/S0160289615000598
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Armed Services Vocational Aptitude Battery (ASVAB); Cognitive Ability; College Major/Field of Study/Courses; Gender Differences; Intelligence; STEM (Science, Technology, Engineering & Mathematics); Test Scores/Test theory/IRT

This research examined sex differences in ability tilt, defined as within-subject differences in math and verbal scores on three tests (SAT, ACT, PSAT). These differences produced math tilt (math>verbal) and verbal tilt (verbal>math). Both types of tilt were correlated with specific abilities (e.g., verbal and math), based on the Armed Services Vocational Aptitude Battery. Tilt was also correlated with college majors in STEM (e.g., science and math) and the humanities (e.g., English and history), and with jobs in STEM and other occupations. Males showed math tilt and STEM preferences, whereas females showed verbal tilt and humanities preferences. For males and females, math tilt predicted math ability and STEM criteria (majors and jobs), and verbal tilt predicted verbal ability and verbal criteria. Tilt scores correlated negatively with competing abilities (e.g., math tilt and verbal ability). The results supported investment theories, which assume that investment in a specific ability boosts similar abilities but retards competing abilities. In addition, the results bolster the validity of tilt, which was unrelated to g but still predicted specific abilities, college majors, and jobs.
Bibliography Citation
Coyle, Thomas R., Anissa Snyder and Miranda C. Richmond. "Sex Differences in Ability Tilt: Support for Investment Theory." Intelligence 50 (May-June 2015): 209-220.
13. Deary, Ian J.
Der, Geoff
Shenkin, Susan D.
Does Mother's IQ Explain the Association Between Birth Weight and Cognitive Ability in Childhood?
Intelligence 33,5 (September-October 2005): 445-454.
Also: http://www.sciencedirect.com/science/article/pii/S0160289605000577
Cohort(s): Children of the NLSY79, NLSY79
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Birthweight; Cognitive Ability; I.Q.; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Peabody Picture Vocabulary Test (PPVT); Test Scores/Test theory/IRT

There is a significant association between birth weight and cognitive test scores in childhood, even among individuals born at term and with normal birth weight. The association is not explained by the child's social background. Here we examine whether mother's cognitive ability accounts for the birth weight–cognitive ability association. We analysed mother and child data from the National Longitudinal Survey of Youth 1979. Random effects models were employed to utilise fully the repeated cognitive tests on the same child, and to include all children of each mother. Mother's score on the Armed Forces Qualification Test (AFQT) was significantly related to child's birth weight. Birth weight was significantly related to the child's scores on the Peabody Individual Achievement Test. This association was attenuated by up to two-thirds after taking into account mother's AFQT score. In this large sample the association between birth weight and cognitive ability was substantially explained by mother's IQ. [ABSTRACT FROM AUTHOR; Copyright 2005 Elsevier]
Bibliography Citation
Deary, Ian J., Geoff Der and Susan D. Shenkin. "Does Mother's IQ Explain the Association Between Birth Weight and Cognitive Ability in Childhood?" Intelligence 33,5 (September-October 2005): 445-454.
14. Deary, Ian J.
Irwing, Paul
Der, Geoff
Bates, Timothy C.
Brother--Sister Differences in the g Factor in Intelligence: Analysis of Full, Opposite-Sex Siblings from the NLSY1979
Intelligence 35,5 (September-October 2007): 451-456.
Also: http://www.sciencedirect.com/science/article/pii/S0160289606001115
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Armed Services Vocational Aptitude Battery (ASVAB); Cognitive Ability; g Factor; Gender Differences; I.Q.; Intelligence; Siblings; Sisters

There is scientific and popular dispute about whether there are sex differences in cognitive abilities and whether they are relevant to the proportions of men and women who attain high-level achievements, such as Nobel Prizes. A recent meta-analysis (Lynn, R., and Irwing, P. (2004). Sex differences on the progressive matrices: a meta-analysis. Intelligence, 32, 481–498.), which suggested that males have higher mean scores on the general factor in intelligence (g), proved especially contentious. Here we use a novel design, comparing 1292 pairs of opposite-sex siblings who participated in the US National Longitudinal Survey of Youth 1979 (NLSY1979). The mental test applied was the Armed Services Vocational Aptitude Battery (ASVAB), from which the briefer Armed Forces Qualification Test (AFQT) scores can also be derived. Males have only a marginal advantage in mean levels of g (less than 7% of a standard deviation) from the ASVAB and AFQT, but substantially greater variance. Among the top 2% AFQT scores, there were almost twice as many males as females. These differences could provide a partial basis for sex differences in intellectual eminence. [Copyright 2007 Elsevier]

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Bibliography Citation
Deary, Ian J., Paul Irwing, Geoff Der and Timothy C. Bates. "Brother--Sister Differences in the g Factor in Intelligence: Analysis of Full, Opposite-Sex Siblings from the NLSY1979." Intelligence 35,5 (September-October 2007): 451-456.
15. Der, Geoff
Batty, G. David
Deary, Ian J.
The Association Between IQ in Adolescence and a Range of Health Outcomes at 40 in the 1979 US National Longitudinal Study of Youth
Intelligence 37,6 (November-December 2009): 573-580.
Also: http://www.sciencedirect.com/science/article/pii/S0160289608001669
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): CESD (Depression Scale); Cognitive Ability; Depression (see also CESD); Health, Mental; Health/Health Status/SF-12 Scale; I.Q.; Intelligence; Intelligence Tests; Morbidity; Mortality

A link between pre-morbid intelligence and all cause mortality is becoming well established, but the aetiology of the association is not understood. Less is known about links with cause specific mortality and with morbidity. The aim of this study is to examine the association between intelligence measured in adolescence and a broad range of health outcomes ascertained at 40 years of age. We use data on 7476 participants in the US National Longitudinal Survey of Youth 1979 who had their cognitive ability measured at baseline and completed the 'Health at 40' interview module between 1998 and 2004. The Health at 40 module includes assessments of general health and depression, nine medically diagnosed conditions, and 33 common health problems. Higher mental test scores were associated with lower depression scores, better general health, significantly lower odds of having five of the nine diagnosed conditions and 15 of the 33 health problems. A health disadvantage of higher cognitive ability was evident for only three of the 33 health problems.
Bibliography Citation
Der, Geoff, G. David Batty and Ian J. Deary. "The Association Between IQ in Adolescence and a Range of Health Outcomes at 40 in the 1979 US National Longitudinal Study of Youth." Intelligence 37,6 (November-December 2009): 573-580.
16. Ganzach, Yoav
A Dynamic Analysis of the Effects of Intelligence and Socioeconomic Background on Job-Market Success
Intelligence 39,2-3 (March-April 2011): 120-129.
Also: http://www.sciencedirect.com/science/article/pii/S0160289611000237
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Career Patterns; Educational Attainment; Intelligence; Mobility; Socioeconomic Background; Wage Growth; Wage Models

We compare the effects of socioeconomic background (SEB) and intelligence on wage trajectories in a dynamic growth modeling framework in a sample that had completed just 12 years of education. I show that the main difference between the two is that SEB affected wages solely by its effect on entry pay whereas intelligence affected wages primarily by its effect on mobility. I argue that a major issue that has been at the center of the debate about the roles of intelligence and SEB in social success -- the difficulty in accurately measuring SEB -- is to a large extent resolved by these results.
Bibliography Citation
Ganzach, Yoav. "A Dynamic Analysis of the Effects of Intelligence and Socioeconomic Background on Job-Market Success." Intelligence 39,2-3 (March-April 2011): 120-129.
17. Ganzach, Yoav
Cognitive Ability and Party Affiliation: The Role of the Formative Years of Political Socialization
Intelligence 61 (March-April 2017): 56-62.
Also: http://www.sciencedirect.com/science/article/pii/S0160289616302677
Cohort(s): Children of the NLSY79, NLSY79, NLSY79 Young Adult
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Cognitive Ability; Intelligence; Peabody Picture Vocabulary Test (PPVT); Political Attitudes/Behaviors/Efficacy

We study the effect of time on the relationship between intelligence and party affiliation in the United States. Our results indicate that time affects this relationship, and that this effect is due to the formative years in which political preferences were developed rather than the time in which the survey was conducted. For people who were born in the 20th century, the later their formative years, the more positive the relationship between intelligence and Democratic, as opposed to Republican, affiliation. The current results shed light on recent conflicting findings about the relationship between intelligence and party affiliation in the US, and suggest that the effect of intelligence on party affiliation changes with time.
Bibliography Citation
Ganzach, Yoav. "Cognitive Ability and Party Affiliation: The Role of the Formative Years of Political Socialization." Intelligence 61 (March-April 2017): 56-62.
18. Ganzach, Yoav
Intelligence and the Rationality of Political Preferences
Intelligence 69 (July-August 2018): 59-70.
Also: https://www.sciencedirect.com/science/article/pii/S0160289617303392
Cohort(s): NLSY79 Young Adult
Publisher: Elsevier
Keyword(s): General Social Survey (GSS); I.Q.; Peabody Picture Vocabulary Test (PPVT); Political Attitudes/Behaviors/Efficacy; Wisconsin Longitudinal Study/H.S. Panel Study (WLS)

I study the relationship between intelligence and the rationality of political preferences. Intelligence is operationalized as achievement in standard mental ability tests, rationality as consistency between political attitudes and political preferences and consistency as the effect of the interaction between intelligence and political attitudes on political preferences. Political preferences are measured by party affiliation -- support for the Democratic versus the Republican Party in the US -- and political attitudes are measured on a conservative-liberal dimension. I analyze three large representative American databases [and] I conclude with a discussion of possible causal processes underlying the observed relationship between intelligence and consistency of political attitudes.
Bibliography Citation
Ganzach, Yoav. "Intelligence and the Rationality of Political Preferences." Intelligence 69 (July-August 2018): 59-70.
19. Ganzach, Yoav
Ellis, Shmuel
Gotlibovski, Chemi
On Intelligence Education and Religious Beliefs
Intelligence 41,2 (March-April 2013): 121-128.
Also: http://www.sciencedirect.com/science/article/pii/S0160289613000020#sec2
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Education; General Social Survey (GSS); Intelligence; Religion; Religious Influences

A number of authors have suggested that education mediates the negative effect of intelligence on religiosity. However, there is very little direct evidence for this mediation, and the indirect evidence is contradictory. The results of the current paper suggest that, by and large, education does not mediate the effect of intelligence on religiosity. However, the results also suggest that since education has a positive effect on religiosity when religious background is strong and a negative effect when religious background is weak, and since intelligence has a positive effect on education, the negative effect of intelligence on religiosity is stronger when religious background is strong than when it is weak. We examine this mediated moderation model in two large, nationally representative, databases.
Bibliography Citation
Ganzach, Yoav, Shmuel Ellis and Chemi Gotlibovski. "On Intelligence Education and Religious Beliefs." Intelligence 41,2 (March-April 2013): 121-128.
20. Ganzach, Yoav
Fried, Itzhak
The Role of Intelligence in the Formation of Well-being: From Job Rewards to Job Satisfaction
Intelligence 40,4 (July-August 2012): 333-342.
Also: http://www.sciencedirect.com/science/article/pii/S0160289612000396
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Intelligence; Job Rewards; Job Satisfaction; Modeling

In a longitudinal study, we investigate the moderating role of intelligence on the effects of intrinsic and extrinsic rewards and intrinsic and extrinsic satisfactions on global job satisfaction. The results support our hypotheses that: (1) intrinsic rewards and intrinsic satisfaction are more strongly related to global job satisfaction among individuals who are higher rather than lower in intelligence; and (2) extrinsic rewards and extrinsic satisfaction are more strongly related to global job satisfaction among individuals who are lower rather than higher in intelligence. We also suggest that these effects could be viewed in terms of a moderated mediation model in which facets' satisfaction mediate the effects of rewards on global satisfaction, and intelligence moderates the relationship between facets' satisfaction and global satisfaction. Implications of the results were discussed.
Bibliography Citation
Ganzach, Yoav and Itzhak Fried. "The Role of Intelligence in the Formation of Well-being: From Job Rewards to Job Satisfaction." Intelligence 40,4 (July-August 2012): 333-342.
21. Ganzach, Yoav
Gotlibovski, Chemi
Intelligence and Religiosity: Within Families and Over Time
Intelligence 41,5 (September-October 2013): 546-552.
Also: http://www.sciencedirect.com/science/article/pii/S0160289613000962
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Intelligence; Religion; Religious Influences; Siblings

We study the effect of intelligence (General Mental Ability) on religiosity using research designs that allow for stronger causal inferences compared to previous research in this area. First, we examine how between-siblings differences in intelligence are related to differences in their religiosity. Second, we examine how intelligence is related to changes in religiosity over time. The results of both designs suggest that intelligence has a strong negative effect on religiosity. In addition, our results also suggest that intelligence interacts with age in determining religiosity: the more intelligent the person, the stronger the negative effect of age on religiosity.
Bibliography Citation
Ganzach, Yoav and Chemi Gotlibovski. "Intelligence and Religiosity: Within Families and Over Time." Intelligence 41,5 (September-October 2013): 546-552.
22. Ganzach, Yoav
Gotlibovski, Chemi
Greenberg, Doron
Pazy, Asya
General Mental Ability and Pay: Nonlinear Effects
Intelligence 41,5 (September-October 2013): 631-637.
Also: http://www.sciencedirect.com/science/article/pii/S0160289613001086
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Cognitive Ability; Earnings; Economic Well-Being; I.Q.; Occupations

While many studies have examined the linear relationship between intelligence and economic success, only few, if any, examined their nonlinear relationships. The current study examines such relationships in a large, nationally representative sample, using pay as an indicator of economic success. The results show that the effect of General Mental Ability (GMA) on pay depends on occupational complexity; the greater the complexity, the stronger the effect. They also show that, by and large, there is a marginally decreasing (concave) effect of GMA on pay. Methodological and practical questions concerning the relationship between cognitive ability and pay are discussed.
Bibliography Citation
Ganzach, Yoav, Chemi Gotlibovski, Doron Greenberg and Asya Pazy. "General Mental Ability and Pay: Nonlinear Effects." Intelligence 41,5 (September-October 2013): 631-637.
23. Garrison, S. Mason
Rodgers, Joseph Lee
Casting Doubt on the Causal Link between Intelligence and Age at First Intercourse: A Cross-generational Sibling Comparison Design Using the NLSY
Intelligence 59 (November-December 2016): 139-156.
Also: http://www.sciencedirect.com/science/article/pii/S0160289616300162
Cohort(s): Children of the NLSY79, NLSY79, NLSY79 Young Adult
Publisher: Elsevier
Keyword(s): Age at First Intercourse; Armed Forces Qualifications Test (AFQT); Digit Span (also see Memory for Digit Span - WISC); Intelligence; Intergenerational Patterns/Transmission; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Peabody Picture Vocabulary Test (PPVT); Siblings

In this study, we use an intergenerational sibling comparison design to investigate the causal link between intelligence and AFI, using the National Longitudinal Survey of Youth 1979 and the NLSY-Children/Young Adult data. We measured maternal IQ using the AFQT, child IQ using PPVT, PIAT, and Digit Span, and AFI, using respondent self-report. Our analytic method used Kenny's (2001) reciprocal standard dyad model. This model supported analyses treating the data as only between-family data (as in most past studies), and also allowed us to include both between- and within-family comparisons. These analyses included two forms, first a comparison of offspring of mothers in relation to maternal IQ, then a comparison of offspring themselves in relation to offspring IQ.

When we evaluated the relationship between maternal/child intelligence and AFI, using a between-family design, we replicated earlier results; smart teens do appear to delay sex. In the within-family analyses, the relationship between intelligence and AFI vanishes for both maternal intelligence and child intelligence. The finding is robust across gender and age. These results suggest that the cause of the intelligence-AFI link is not intelligence per se, but rather differences between families (parental education, SES, etc.) that correlate with family-level (but not individual-level) intelligence.

Bibliography Citation
Garrison, S. Mason and Joseph Lee Rodgers. "Casting Doubt on the Causal Link between Intelligence and Age at First Intercourse: A Cross-generational Sibling Comparison Design Using the NLSY." Intelligence 59 (November-December 2016): 139-156.
24. Hartmann, Peter
Kruuse, Nanna Hye Sun
Nyborg, Helmuth
Testing the Cross-Racial Generality of Spearman's Hypothesis in Two Samples
Intelligence 35,1 (January-February 2007): 47-57.
Also: http://www.sciencedirect.com/science/article/pii/S0160289606000481
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Armed Services Vocational Aptitude Battery (ASVAB); Birth Outcomes; g Factor; Hispanics; Intelligence; Racial Differences

Spearman's hypothesis states that racial differences in IQ between Blacks (B) and Whites (W) are due primarily to differences in the "g" factor. This hypothesis is often confirmed, but it is less certain whether it generalizes to other races. We therefore tested its cross-racial generality by comparing American subjects of European descent (W) to American Hispanics (H) in two different databases. The first [Centers for Disease Control (1988). Health status of Vietnam veterans. "Journal of the American Medical Association" 259, 2701-2719; Centers for Disease Control (1989). "Health status of Vietnam veterans: Vol IV. Psychological and neuropsychological evaluation." Atlanta, Georgia: Center for Environmental Health and Injury Control] contains 4462 middle-aged Armed Services Veterans males, and the second database (NLSY1979) holds 11,625 young male and female adults. Both samples are fairly representative of the general American population. Race differences in general intelligence "g" were calculated and vectors of test scores were correlated with the vectors of the tests' "g" loadings, following Jensen [Jensen, A. R. (1998). "The "g" factor." Westport, CT: Praeger]. W scored about 0.8 S.D. above H. The racial difference on the tests correlated significantly with the "g"-loadings of the tests in the VES database, but less so in the NLSY database. We therefore conclude that the present study supports, but does not unequivocally verify, the cross-racial generality of the Spearman's hypothesis.
Bibliography Citation
Hartmann, Peter, Nanna Hye Sun Kruuse and Helmuth Nyborg. "Testing the Cross-Racial Generality of Spearman's Hypothesis in Two Samples ." Intelligence 35,1 (January-February 2007): 47-57.
25. Hartmann, Peter
Reuter, Martin
Spearman's "Law of Diminishing Returns" Tested with Two Methods
Intelligence 34,1 (January-February 2006): 47-62.
Also: http://www.sciencedirect.com/science/article/pii/S0160289605000632
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Armed Services Vocational Aptitude Battery (ASVAB); Children; Computer Assisted Personal Interviewing (CAPI); g Factor; Test Scores/Test theory/IRT

Spearman's "Law of Diminishing Returns" with regard to ability is tested in a dataset from the National Longitudinal Study of Youth. The dataset consisted of a sample of 6980 children aged 12–16 from the 1997 cohort. The subjects were tested with a computer administrated adaptive format of the Armed Services Vocational Aptitude Battery consisting of 12 subtests

Spearman's "Law of Diminishing Returns" was tested by two methods both dividing the sample into Low/High ability based either on the total score on the test or on the score one of the 12 subtests. Subsequently the ability groups were factor analysed separately. The eigenvalue of the first principal component and the first principal axis factor, and the average inter-correlation of the subtests were used as estimates of the g saturation and compared across groups.

The study could not confirm Spearman's "Law of Diminishing Returns" for any of the methods applied and did not find any relevant differences across methods applied.

Bibliography Citation
Hartmann, Peter and Martin Reuter. "Spearman's "Law of Diminishing Returns" Tested with Two Methods." Intelligence 34,1 (January-February 2006): 47-62.
26. Jokela, Markus
Flow of Cognitive Capital across Rural and Urban United States
Intelligence 46 (September-October 2014): 47-53.
Also: http://www.sciencedirect.com/science/article/pii/S0160289614000750
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Cognitive Ability; Educational Attainment; Geocoded Data; Geographical Variation; Income; Migration; Mobility, Residential; Rural Areas; Urbanization/Urban Living

Socioeconomic status and other socio-demographic factors have been associated with selective residential mobility across rural and urban areas, but the role of psychological characteristics in selective migration has been studied less. The current study used 16-year longitudinal data from the U.S. National Longitudinal Survey of Youth 1979 (NLSY79) to examine whether cognitive ability assessed at age 15–23 predicted subsequent urban/rural migration between ages 15 and 39 (n = 11,481). Higher cognitive ability was associated with selective rural-to-urban migration (12 percentile points higher ability among those moving from rural areas to central cities compared to those staying in rural areas) but also with higher probability of moving away from central cities to suburban and rural areas (4 percentile points higher ability among those moving from central cities to suburban areas compared to those staying in central cities). The mobility patterns associated with cognitive ability were largely but not completely mediated by adult educational attainment and income. The findings suggest that selective migration contributes to differential flow of cognitive ability levels across urban and rural areas in the United States.
Bibliography Citation
Jokela, Markus. "Flow of Cognitive Capital across Rural and Urban United States." Intelligence 46 (September-October 2014): 47-53.
27. Koenig, Katherine A.
Frey, Meredith C.
Detterman, Douglas K.
ACT and General Cognitive Ability
Intelligence 36,2 (March-April 2008): 153-160.
Also: http://www.sciencedirect.com/science/article/pii/S0160289607000487
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Armed Services Vocational Aptitude Battery (ASVAB); g Factor; Gender Differences; I.Q.; Labor Supply; Mobility, Occupational; Modeling; Test Scores/Test theory/IRT; Wage Equations; Wages, Women

Research on the SAT has shown a substantial correlation with measures of g such as the Armed Services Vocational Aptitude Battery (ASVAB). Another widely administered test for college admission is the American College Test (ACT). Using the National Longitudinal Survey of Youth 1979, measures of g were derived from the ASVAB and correlated with ACT scores for 1075 participants. The resulting correlation was .77. The ACT also shows significant correlations with the SAT and several standard IQ tests. A more recent sample (N =149) consisting of ACT scores and the Raven's APM shows a correlation of .61 between Raven's-derived IQ scores and Composite ACT scores. It appears that ACT scores can be used to accurately predict IQ in the general population. [Copyright 2008 Elsevier] Copyright of Intelligence is the property of Elsevier Science Publishing Company, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts)
Bibliography Citation
Koenig, Katherine A., Meredith C. Frey and Douglas K. Detterman. "ACT and General Cognitive Ability." Intelligence 36,2 (March-April 2008): 153-160.
28. Lyerly, Jordan E.
Reeve, Charlie L.
Evaluating the Unique Effects of Cognitive Ability and Parental Socioeconomic Status on Adult Dietary Behaviors and Receipt of Preventive Health Services
Intelligence 47 (November-December 2014): 113-121.
Also: http://www.sciencedirect.com/science/article/pii/S0160289614001366
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Armed Services Vocational Aptitude Battery (ASVAB); Cognitive Ability; Educational Attainment; Health Care; Income; Nutritional Status/Nutrition/Consumption Behaviors; Parental Influences; Socioeconomic Status (SES)

Some research has shown that both cognitive ability and parental socioeconomic status (parental SES) predict dietary behaviors and receipt of preventive health services later in life. However, previous research has not attempted to disentangle these effects while also examining important mediators such as education level and income. Based on a sample of 4078 individuals drawn from the National Longitudinal Survey of Youth 1979, we examined the unique effects of g and parental SES on adult dietary behaviors and receipt of preventive health services. Overall, the results suggest that there is essentially little direct unique effect of cognitive ability or parental SES on adult dietary behaviors and receipt of preventive health services. However, the total effects of cognitive ability and parental SES on adult dietary behaviors and receipt of preventive health services showed that higher levels of cognitive ability and parental SES were associated with healthier dietary habits and receipt of health services due to their effects on educational attainment and adult income. The findings may have implications for health education materials and access to healthcare.
Bibliography Citation
Lyerly, Jordan E. and Charlie L. Reeve. "Evaluating the Unique Effects of Cognitive Ability and Parental Socioeconomic Status on Adult Dietary Behaviors and Receipt of Preventive Health Services." Intelligence 47 (November-December 2014): 113-121.
29. Meisenberg, Gerhard
The Reproduction of Intelligence
Intelligence 38,2 (March-April 2010): 220-230.
Also: http://www.sciencedirect.com/science/article/pii/S016028961000005X
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Armed Services Vocational Aptitude Battery (ASVAB); Cognitive Ability; Education; Fertility; Gender Attitudes/Roles; I.Q.; Intelligence; Racial Differences; Religion

Although a negative relationship between fertility and education has been described consistently in most countries of the world, less is known about the relationship between intelligence and reproductive outcomes. Also the paths through which intelligence influences reproductive outcomes are uncertain. The present study uses the NLSY79 to analyze the relationship of intelligence measured in 1980 with the number of children reported in 2004, when the respondents were between 39 and 47 years old. Intelligence is negatively related to the number of children, with partial correlations (age controlled) of −.156, −.069, −.235 and −.028 for White females, White males, Black females and Black males, respectively. This effect is related mainly to the g-factor. It is mediated in part by education and income, and to a lesser extent by the more “liberal” gender attitudes of more intelligent people. In the absence of migration and with constant environment, genetic selection would reduce the average IQ of the US population by about .8 points per generation.
Bibliography Citation
Meisenberg, Gerhard. "The Reproduction of Intelligence." Intelligence 38,2 (March-April 2010): 220-230.
30. Murray, Charles A.
Changes Over Time in the Black–White Difference on Mental Tests: Evidence from the Children of the 1979 Cohort of the National Longitudinal Survey of Youth
Intelligence 34,6 (November 2006): 527-540.
Also: http://www.sciencedirect.com/science/article/pii/S016028960600078X
Cohort(s): Children of the NLSY79
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Children, Academic Development; I.Q.; Intelligence; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Peabody Picture Vocabulary Test (PPVT); Racial Differences; Variables, Independent - Covariate

Data for three Peabody achievement tests and for the Peabody picture vocabulary test administered to children of women in the 1979 cohort of the National Longitudinal Survey of Youth show that the black–white difference did not diminish for this sample of children born from the mid 1970s through the mid 1990s. This finding persists after entering covariates for the child's age and family background variables. It is robust across alternative samples and specifications of the model. The analysis supplements other evidence that shows no narrowing of the black–white difference in academic achievement tests since the late 1980s and is inconsistent with recent evidence that narrowing occurred in IQ standardizations during the same period. A hypothesis for reconciling this inconsistency is proposed.
Bibliography Citation
Murray, Charles A. "Changes Over Time in the Black–White Difference on Mental Tests: Evidence from the Children of the 1979 Cohort of the National Longitudinal Survey of Youth." Intelligence 34,6 (November 2006): 527-540.
31. Nyborg, Helmuth
Sex Differences Across Different Racial Ability Levels: Theories of Origin and Societal Consequences
Intelligence 52 (September-October 2015): 44-62.
Also: http://www.sciencedirect.com/science/article/pii/S0160289615000525
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Armed Services Vocational Aptitude Battery (ASVAB); Gender Differences; I.Q.; Racial Differences

Jensen (1971) found that black girls score 3 IQ points higher than black boys, and white boys 1.5 IQ points higher than white girls. He, nevertheless, concluded that this did not support his Race × Sex × Ability interaction theory. Jensen (1998) further analyzed data, some from the National Longitudinal Survey of Youth (NLSY79), and suggested that there is no sex difference in general intelligence, g. Other studies have questioned Jensen's null sex difference theory.

The present study tested both theories with data from the ensuring NLSY97 survey, which represents the 15 + million 12–17 year old adolescents living in the US in 1997.

Total sample analyses confirmed the existence of significant inverse white-black IQ sex differences, and disconfirmed the null sex difference theory.

Separate race-age analyses demonstrated, however, that robust IQ sex differences materialize only after age 16, with no white-black interaction. At age 17, female IQ trails male by 3.6-7.03 points in three races, respectively.

Classical IQ probability curves foretell that more males than females will enter the highest echelons of society, irrespective of race, and white Male/Female ratios at IQ 145 successfully predicted real-life sex differences in educational and occupational achievement. White males with IQ 55 can be expected to run a very high risk of encountering severe achievement problems, a risk shared to some extent with Hispanic male, but black females with this low IQ can be expected to perform worse than black males.

Bibliography Citation
Nyborg, Helmuth. "Sex Differences Across Different Racial Ability Levels: Theories of Origin and Societal Consequences." Intelligence 52 (September-October 2015): 44-62.
32. Nyborg, Helmuth
The Intelligence-Religiosity Nexus: A Representative Study of White Adolescent Americans
Intelligence 37,1 (January-February 2009): 81-93.
Also: http://www.sciencedirect.com/science/article/pii/S0160289608001013
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Cognitive Development; Education; g Factor; I.Q.; Intelligence; Religion; Religious Influences

The present study examined whether IQ relates systematically to denomination and income within the framework of the g nexus, using representative data from the National Longitudinal Study of Youth (NLSY97). Atheists score 1.95 IQ points higher than Agnostics, 3.82 points higher than Liberal persuasions, and 5.89 IQ points higher than Dogmatic persuasions. Denominations differ significantly in IQ and income. Religiosity declines between ages 12 to 17. It is suggested that IQ makes an individual likely to gravitate toward a denomination and level of achievement that best fit his or hers particular level of cognitive complexity. Ontogenetically speaking this means that contemporary denominations are rank ordered by largely hereditary variations in brain efficiency (i.e. IQ). In terms of evolution, modern Atheists are reacting rationally to cognitive and emotional challenges, whereas Liberals and, in particular Dogmatics, still rely on ancient, pre-rational, supernatural and wishful thinking.
Bibliography Citation
Nyborg, Helmuth. "The Intelligence-Religiosity Nexus: A Representative Study of White Adolescent Americans." Intelligence 37,1 (January-February 2009): 81-93.
33. Rodgers, Joseph Lee
Rowe, David C.
May, Kim
DF Analysis of NLSY IQ/Achievement Data: Nonshared Environmental Influences
Intelligence 19,2 (September-October 1994): 157-177.
Also: http://www.sciencedirect.com/science/article/pii/0160289694900116
Cohort(s): Children of the NLSY79, NLSY79
Publisher: Economics Department, Moore School of Business, University of Soutn Carolina
Keyword(s): Children; Cognitive Ability; Genetics; Home Environment; Home Observation for Measurement of Environment (HOME); I.Q.; Intelligence; Kinship; Memory for Digit Span (WISC) - also see Digit Span; Methods/Methodology; Modeling; Pairs (also see Siblings); Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Peabody Picture Vocabulary Test (PPVT); Siblings; Simultaneity

Permission to reprint the abstract has not been received from the publisher.

An adaptation of DF (DeFries and Fulker, 1985) is fitted to achievement measures from 5-12-year-old children from the National Longitudinal Survey of Youth (NLSY). This adaptation can simultaneously account for genetic shared environmental, and non shared environmental influences within the same model. The NLSY contains information to link kinship pairs at multiple levels including cousins, half-siblings, full-siblings, and twins. One thousand forty-four pairs were identified by a kinship-linking algorithm. From five specific measures of intellectual ability we estimated median heritability. We then tested for the presence of several specific non shared influences. As predicted differences between two related children in the number of books owned were related to differences in reading recognition scores and trips to the museum were related to a measure of mathematical ability. A general measure of the home environment accounted for non shared environmental variance in several specific measures of intelligence and in a general measure of cognitive ability.
Bibliography Citation
Rodgers, Joseph Lee, David C. Rowe and Kim May. "DF Analysis of NLSY IQ/Achievement Data: Nonshared Environmental Influences." Intelligence 19,2 (September-October 1994): 157-177.
34. Rodgers, Joseph Lee
Wanstrom, Linda
Identification of a Flynn Effect in the NLSY: Moving from the Center to the Boundaries
Intelligence 35,2 (March-April 2007): 187-196.
Also: http://www.sciencedirect.com/science/article/pii/S0160289606000717
Cohort(s): Children of the NLSY79
Publisher: Elsevier
Keyword(s): Digit Span (also see Memory for Digit Span - WISC); Flynn Effect; I.Q.; Intelligence; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Peabody Picture Vocabulary Test (PPVT)

The Flynn Effect [Flynn, J.R. (1984). The mean IQ of Americans: Massive gains 1932 to 1978. Psychological Bulletin 95, 29-51.] is an increase in IQ of around .33 points per year, observed in developed (and some developing) countries during the past century. It emerges from problem solving and other non-verbal components of IQ. The cause has been argued and theories proposed. Rodgers [Rodgers, J.L. (1998). A critique of the Flynn Effect: Massive IQ gains, methodological artifacts, or both? Intelligence 26, 337-356.] noted that the search for causes has preceded specification of the nature of the effect. Our study uses a national sample of U.S. children to test for the Flynn Effect in PIAT-Math, PIAT-Reading Recognition, PIAT-Reading Comprehension, Digit Span, and PPVT. An effect of the predicted magnitude was observed for PIAT-Math when maternal IQ was controlled. This finding in a large representative sample with thousands of variables supports more careful evaluation of the Flynn Effect, in demographic, geographic, environmental, and biological domains. © 2006 Elsevier Inc. All rights reserved.
Bibliography Citation
Rodgers, Joseph Lee and Linda Wanstrom. "Identification of a Flynn Effect in the NLSY: Moving from the Center to the Boundaries ." Intelligence 35,2 (March-April 2007): 187-196.
35. Rowe, David C.
Cleveland, Hobart Harrington
Academic Achievement in Blacks and Whites: Are the Developmental Processes Similar?
Intelligence 23,3 (November-December 1996): 205-228.
Also: http://www.sciencedirect.com/science/article/pii/S0160289696900045
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Black Studies; Child Development; Educational Attainment; Genetics; Intelligence; Pairs (also see Siblings); Racial Differences; Racial Studies; Siblings

Genetic and environmental influences on academic achievement were investigated in four groups of siblings: (1) White full siblings, (2) White half-siblings, (3) Black full siblings, and (4) Black half-siblings. Our expectation was that the variances and covariances among three achievement tests would have the same structure across the four groups. This expectation was confirmed by a quantitative genetic model that imposed equal factor loadings across groups. This best fitting model had two factors: a Genetic factor representing genetic variation and a Shared Environment factor representing environmental differences among families. Reading recognition, reading comprehension, and mathematics tests all loaded on the Genetic factor, but primarily mathematics loaded on the Shared Environment factor. The quantitative genetic model was next fit to the achievement test means. Its successful fit suggested that the genetic and environmental influences involved in producing individual variation were the same as those producing the group-mean differences. In this sample, genes accounted for 66% to 74% of the observed group difference in verbal achievement and 36% of the difference in mathematics achievement. Shared environment accounted for the remainder, 34% to 26% of the difference in verbal achievement and 64% of that in mathematics achievement.
Bibliography Citation
Rowe, David C. and Hobart Harrington Cleveland. "Academic Achievement in Blacks and Whites: Are the Developmental Processes Similar? ." Intelligence 23,3 (November-December 1996): 205-228.
36. Rowe, David C.
Vesterdal, Wendy J.
Rodgers, Joseph Lee
Herrnstein's Syllogism: Genetic and Shared Environmental Influences on IQ, Education, and Income
Intelligence 26,4 (November 1998): 405-423.
Also: http://www.sciencedirect.com/science/article/pii/S0160289699000082
Cohort(s): NLSY79
Publisher: Economics Department, Moore School of Business, University of Soutn Carolina
Keyword(s): Education; Genetics; I.Q.; Income; Income Distribution; Intelligence; Kinship; Modeling, Biometric; Siblings

Permission to reprint the abstract has not been received from the publisher.

Genotypes may influence the phenotypic associations among IQ, education, and income. To investigate this hypothesis, we believe that the appropriate methodology requires estimation of genetic and environmental influences using data able to separate these influences. The National Longitudinal Survey of Youth (NLSY) is a nationally representative sample that contains genetically-informative full- and half-siblings (28-35 years old in 1992; Ns = 1943 full-siblings, 129 half-siblings). A biometric genetic model was fit that estimated the shared environmental and genetic variance components of IQ, years of education, and hourly income. The total heritabilities were 0.64 for IQ, 0.68 for education, and 0.42 for income. Heritabilities due to a common genetic factor were 0.35 for IQ, 0.52 for education, and 0.12 for income. Environmental influences due to a common shared environmental factor were 0.23 for IQ, 0.18 for education, and 0.08 for income. The model predicted a correlation of 0.63 between IQ and education and 0.34 between IQ and income. Sixty-eight percent of the former and 59% of the latter was genetically mediated; the remainder was mediated by common shared environment. These findings suggest that social inequality in the United States has its origin in both genetically-based traits and in different environmental backgrounds.
Bibliography Citation
Rowe, David C., Wendy J. Vesterdal and Joseph Lee Rodgers. "Herrnstein's Syllogism: Genetic and Shared Environmental Influences on IQ, Education, and Income." Intelligence 26,4 (November 1998): 405-423.
37. Schult, Johannes
Sparfeldt, Jorn R.
Do Non-g Factors of Cognitive Ability Tests Align with Specific Academic Achievements? A Combined Bifactor Modeling Approach
Intelligence 59 (November-December 2016): 96-102.
Also: http://www.sciencedirect.com/science/article/pii/S0160289616302422
Cohort(s): NLSY97
Publisher: Elsevier
Keyword(s): Aptitude; Armed Services Vocational Aptitude Battery (ASVAB); Educational Attainment; Grade Point Average (GPA)/Grades; Intelligence; Test Scores/Test theory/IRT

Bifactor models can clarify how general and specific intelligence factors relate to general and specific academic achievements. By modeling specific group factors that are orthogonal to the general factors one can establish systematic correlations between corresponding non-g residuals of general intelligence and achievement factors. Using data from the National Longitudinal Survey of Youth 1997 (NLSY97; n = 2155), bifactor models were estimated for cognitive ability tests (intelligence, scholastic aptitude) and high school grade point averages (GPA), presuming group factors for numeric/mathematics and for verbal/language content, respectively. The three general factors (intelligence, scholastic aptitude, GPA) were highly correlated. The group factors evidenced convergent validity for numeric abilities and mathematics achievement; the remaining group factor correlations were small. The results demonstrate that besides substantial correlations of the general factors, specific non-g abilities can be successfully linked to specific group factors of academic achievement.
Bibliography Citation
Schult, Johannes and Jorn R. Sparfeldt. "Do Non-g Factors of Cognitive Ability Tests Align with Specific Academic Achievements? A Combined Bifactor Modeling Approach." Intelligence 59 (November-December 2016): 96-102.
38. van den Oord, Edwin J. C. G.
Rowe, David C.
A Cousin Study of Associations between Family Demographic Characteristics and Children's Intellectual Ability
Intelligence 27,3 (September 1999): 251-266.
Also: http://www.sciencedirect.com/science/article/pii/S0160289699000227
Cohort(s): Children of the NLSY79
Publisher: Elsevier
Keyword(s): Age at First Birth; Educational Attainment; Family Studies; Fathers, Absence; I.Q.; Memory for Digit Span (WISC) - also see Digit Span; Mothers, Education; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Peabody Picture Vocabulary Test (PPVT); Poverty; Self-Esteem; Siblings; Welfare

Cousins and siblings from the National Longitudinal Survey of Youth (NLSY) were used to evaluate for several frequently studied environmental variables, the null-hypothesis that correlations with children's IQs represented causal effects. For the majority of the tests the null-hypothesis had to be rejected. Cousin correlations for age [of] mother at the birth of her first child, maternal self-esteem, highest grade completed by the mother, highest grade completed by the father, family poverty status, marital status of the mother, and number of children, suggested that these associations may for an important part be spurious and confounded by third variables that are shared by cousins and affect both the children's home environment as well as their intellectual abilities. Results for quality of the home environment were more equivocal and suggested at least smaller effects of third variables.
Bibliography Citation
van den Oord, Edwin J. C. G. and David C. Rowe. "A Cousin Study of Associations between Family Demographic Characteristics and Children's Intellectual Ability." Intelligence 27,3 (September 1999): 251-266.
39. van den Oord, Edwin J. C. G.
Rowe, David C.
An Examination of Genotype-environment Interactions for Academic Achievement in an U.S. National Longitudinal Survey
Intelligence 25,3 (1997): 205-228.
Also: http://www.sciencedirect.com/science/article/pii/S016028969790043X
Cohort(s): Children of the NLSY79, NLSY79
Publisher: Elsevier
Keyword(s): Educational Attainment; Ethnic Groups/Ethnicity; Fathers, Absence; Genetics; Home Observation for Measurement of Environment (HOME); Kinship; Marital Status; Peabody Individual Achievement Test (PIAT- Math); Peabody Individual Achievement Test (PIAT- Reading); Poverty; Siblings; Welfare

We examined whether genetic and environmental effects on academic achievement changed as a function of the quality of the children's environment. The study included a variety of observed environmental measures such as parental cognitive stimulation and poverty level, longitudinal information about previous environmental conditions, and a larger than average number of children who grew up in deprived environments. The sample consisted of 1664 pairs of full siblings, 366 pairs of half siblings, and 752 pairs of cousins who were on average 9.58 years old. Both a simple descriptive approach as well as significance tests performed with multilevel regression analyses showed little evidence for genotype-environment interactions. There was only a slight trend consisting of a linear decrease of total variance or nonshared environmental effects from deprived to good environments.
Bibliography Citation
van den Oord, Edwin J. C. G. and David C. Rowe. "An Examination of Genotype-environment Interactions for Academic Achievement in an U.S. National Longitudinal Survey." Intelligence 25,3 (1997): 205-228.
40. Vining, Daniel R.
On the Possibility of the Reemergence of a Dysgenic Trend with Respect to Intelligence in American Fertility Differentials
Intelligence 6,3 (July-September 1982): 241-264.
Also: http://www.sciencedirect.com/science/article/pii/0160289682900022
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Birth Rate; Children; Family Influences; Fertility; I.Q.

This paper examines the relationship between IQ and fertility in the NLSY, a sample of men and women aged 25-34 as of the late l970s. The major finding of previous studies was that the IQ/fertility relationship is slightly positive, contrary to expectations though confirmatory of the so-called Eugenic Hypothesis. The working hypothesis is that this finding is special to the cohort chosen for study, i. e., one whose child-bearing took place during a period of rising birth rates. In periods of rising birth rates, persons with higher intelligence tend to have fertility equal to, if not exceeding, that of the population as a whole. In periods of falling birth rates, the opposite is the case. This thesis is generally supported by the data set described above. Fertility differentials to date within the post-World War II cohort, which entered its reproductive years during a period of falling birth rates, show a negative relationship between intelligence and fertility. The relationship is less negative for white men than for white women and for white women than for black women (black men are omitted from this study due to deficiencies in the data). The stated intentions of this cohort with respect to future fertility, if realized, will moderate the degree of this relationship, particularly for whites, but not change its sign.
Bibliography Citation
Vining, Daniel R. "On the Possibility of the Reemergence of a Dysgenic Trend with Respect to Intelligence in American Fertility Differentials." Intelligence 6,3 (July-September 1982): 241-264.
41. Wilmoth, Daniel R.
Intelligence and Past Use of Recreational Drugs
Intelligence 40,1 (January-February 2012): 15-22.
Also: http://www.sciencedirect.com/science/article/pii/S016028961100119X#sec3
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Alcohol Use; Armed Forces Qualifications Test (AFQT); Cigarette Use (see Smoking); Drug Use; I.Q.; Intelligence

One motivation for trying recreational drugs is the desire for novel experiences. More intelligent people tend to value novelty more highly and may therefore be more likely to have tried recreational drugs. Using data from a national survey, it is shown that intelligence tends to be positively related to the probabilities of having tried alcohol, marijuana, cocaine and several other recreational drugs. Evidence is also presented that those relationships typically disappear or change sign at high levels of intelligence. These patterns persist after accounting for a wide range of personal characteristics.
Bibliography Citation
Wilmoth, Daniel R. "Intelligence and Past Use of Recreational Drugs." Intelligence 40,1 (January-February 2012): 15-22.
42. Woodley, Michael A.
Reeve, Charlie L.
Kanazawa, Satoshi
Meisenberg, Gerhard
Fernandes, Heitor B.F.
Cabeza de Baca, Tomas
Contemporary Phenotypic Selection on Intelligence is (mostly) Directional: An Analysis of Three, Population Representative Samples
Intelligence 59 (November-December 2016): 109-114.
Also: http://www.sciencedirect.com/science/article/pii/S0160289616300915
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Armed Services Vocational Aptitude Battery (ASVAB); Britain, British; Fertility; Gender Differences; I.Q.; Project Talent; Racial Differences

Three large and nationally representative datasets (NCDS, N = 5225, NLSY79, N = 7598 and Project Talent, N = 76,150) are here examined in order to determine if models incorporating negative quadratic effects of IQ on fertility (which would indicate the presence of stabilizing phenotypic selection) improve model fit, relative to ones that only consider linear effects (which indicate directional phenotypic selection). Also considered were possible interactions among these terms and sex and race. For two datasets (NCDS and NLSY79) the best fitting models did not include quadratic terms, however significant sex*IQ and race*IQ interactions were found respectively. Only in Project Talent did the inclusion of a quadratic effect (along with IQ*sex and IQ2* sex interactions) yield the best-fitting model. In this instance a small magnitude, significant negative quadratic term was found in addition to a larger magnitude linear term. Post hoc power analysis revealed that power was lacking in the two smaller samples (NCDS and NLSY′79) to detect the quadratic term, however the best fitting and most parsimonious models selected for these datasets did not include the quadratic term. The quadratic terms were furthermore several times smaller in magnitude than the linear terms in all models incorporating both terms. This indicates that stabilizing phenotypic selection is likely only very weakly present in these datasets. The dominance of linear effects across samples therefore suggests that phenotypic selection on IQ in these datasets is principally directional, although the magnitude of selection is relatively small, with IQ explaining at most 1% of the variance in fertility.
Bibliography Citation
Woodley, Michael A., Charlie L. Reeve, Satoshi Kanazawa, Gerhard Meisenberg, Heitor B.F. Fernandes and Tomas Cabeza de Baca. "Contemporary Phenotypic Selection on Intelligence is (mostly) Directional: An Analysis of Three, Population Representative Samples." Intelligence 59 (November-December 2016): 109-114.
43. Wraw, Christina
Deary, Ian J.
Der, Geoff
Gale, Catharine R.
Intelligence in Youth and Mental Health at Age 50
Intelligence 58 (September-October 2016): 69-79.
Also: http://www.sciencedirect.com/science/article/pii/S0160289616300356
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Depression (see also CESD); Health, Mental; Health/Health Status/SF-12 Scale; Intelligence; Sleep; Socioeconomic Status (SES)

Background: Few cognitive epidemiology studies on mental health have focused on the links between pre-morbid intelligence and self-reports of common mental disorders, such as depression, sleep difficulties, and mental health status. The current study examines these associations in 50-year-old adults.

Methods: The study uses data from the 5793 participants in the National Longitudinal Survey of Youth 1979 cohort (NLSY-79) who responded to questions on mental health at age 50 and had IQ measured with the Armed Forces Qualification Test (AFQT) when they were aged between 15 and 23 years in 1980. Mental health outcomes were: life-time diagnosis of depression; the mental component score of the 12-item short-form Health Survey (SF-12); the 7-item Center for Epidemiological Studies Depression Scale (CES-D); and a summary measure of sleep difficulty.

Bibliography Citation
Wraw, Christina, Ian J. Deary, Geoff Der and Catharine R. Gale. "Intelligence in Youth and Mental Health at Age 50." Intelligence 58 (September-October 2016): 69-79.
44. Wraw, Christina
Deary, Ian J.
Gale, Catharine R.
Der, Geoff
Intelligence in Youth and Health at Age 50
Intelligence 53 (November-December 2015): 23-32.
Also: http://www.sciencedirect.com/science/article/pii/S0160289615001014
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Armed Forces Qualifications Test (AFQT); Health, Chronic Conditions; Health/Health Status/SF-12 Scale; Intelligence

Background: The link between intelligence in youth and all-cause mortality in later-life is well established. To better understand this relationship, the current study examines the links between pre-morbid intelligence and a number of specific health outcomes at age 50 using the NLSY-1979 cohort.

Methods: Participants were the 5793 participants in the NLSY-79 who responded to questions about health outcomes at age 50. Sixteen health outcomes were examined: two were summary measures (physical health and functional limitation), 9 were diagnosed illness conditions, 4 were self-reported conditions, and one was a measure of general health status. Linear and logistic regressions were used, as appropriate, to examine the relationship between intelligence in youth and the health outcomes. Age, sex and both childhood and adult SES, and its sub-components – income, education, & occupational prestige – are all adjusted for separately.

Bibliography Citation
Wraw, Christina, Ian J. Deary, Catharine R. Gale and Geoff Der. "Intelligence in Youth and Health at Age 50." Intelligence 53 (November-December 2015): 23-32.
45. Wraw, Christina
Der, Geoff
Gale, Catharine R.
Deary, Ian J.
Intelligence in Youth and Health Behaviours in Middle Age
Intelligence 69 (July-August 2018): 71-86.
Also: https://www.sciencedirect.com/science/article/pii/S0160289617302672
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Alcohol Use; Armed Forces Qualifications Test (AFQT); Exercise; Health/Health Status/SF-12 Scale; Intelligence; Nutritional Status/Nutrition/Consumption Behaviors; Smoking (see Cigarette Use)

Objective: We investigated the association between intelligence in youth and a range of health-related behaviours in middle age.

Method: Participants were the 5347 men and women who responded to the National Longitudinal Survey of Youth 1979 (NLSY-79) 2012 survey. IQ was recorded with the Armed Forces Qualification Test (AFQT) when participants were aged 15 to 23 years of age. Self-reports on exercise (moderate activity, vigorous activity, and strength training), dietary, smoking, drinking, and oral health behaviours were recorded when participants were in middle age (mean age = 51.7 years). A series of regression analyses tested for an association between IQ in youth and the different health related behaviours in middle age, while adjusting for childhood socio-economic status (SES) and adult SES.

Conclusion: In the present study, a higher IQ in adolescence was associated with a number of healthier behaviours in middle age. In contrast to these results, a few associations were also identified between higher intelligence and behaviours that may or may not be linked with poor health (i.e. skipping meals and snacking between meals) and with behaviours that are known to be linked with poor health (i.e. drinking alcohol and the number of cigarettes smoked). To explore mechanisms of association, future studies could test for a range of health behaviours as potential mediators between IQ and morbidity or mortality in later life.

Bibliography Citation
Wraw, Christina, Geoff Der, Catharine R. Gale and Ian J. Deary. "Intelligence in Youth and Health Behaviours in Middle Age." Intelligence 69 (July-August 2018): 71-86.
46. Zagorsky, Jay L.
Do You Have to be Smart to be Rich? The Impact of IQ on Wealth, Income and Financial Distress
Intelligence 35,5 (September-October 2007): 489-501.
Also: http://www.sciencedirect.com/science/article/pii/S0160289607000219
Cohort(s): NLSY79
Publisher: Elsevier
Keyword(s): Bankruptcy; I.Q.; Income; Intelligence; Test Scores/Test theory/IRT; Wealth

How important is intelligence to financial success? Using the NLSY79, which tracks a large group of young U.S. baby boomers, this research shows that each point increase in IQ test scores raises income by between $234 and $616 per year after holding a variety of factors constant. Regression results suggest no statistically distinguishable relationship between IQ scores and wealth. Financial distress, such as problems paying bills, going bankrupt or reaching credit card limits, is related to IQ scores not linearly but instead in a quadratic relationship. This means higher IQ scores sometimes increase the probability of being in financial difficulty.
Bibliography Citation
Zagorsky, Jay L. "Do You Have to be Smart to be Rich? The Impact of IQ on Wealth, Income and Financial Distress." Intelligence 35,5 (September-October 2007): 489-501.