What is a good g?

Jensen, Arthur R.; Weng, Li-Jen

doi:10.1016/0160-2896(94)90029-9

Cited by 248 publications

(172 citation statements)

References 29 publications

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“…These are hierarchical models in which the influence of a General factor is via the group factors, which in turn directly influence the variables, and nested models in which the General factor acts independently and directly on the variables. Though it is clear that these two forms of models are not identical and posit different structures by which a General factor exerts its influence, it has been noted that the general interpretation of each of the models is the same (Gustafsson and Balke, 1993) and that both are equally satisfactory for estimating the influence of a General factor (Jensen and Weng, 1994). Empirical assessment of the identification of a hierarchical bifactor model with a somewhat complex factor structure (reading measures loading onto General, Verbal, and Reading factors) indicated that additional constraints beyond those necessary for identification of a nested Bifactor model would be required (constraints among the loadings of the group factors on the General factor) making interpretation of a hierarchical model restrictive and somewhat uninformative.…”

Section: General Statistical Approach and Model Fittingmentioning

confidence: 99%

“…Consistent with the dominant theoretical perspective of the phenotypic structure of intelligence, several studies have suggested that a genetic General factor as well as genetic group and specific influences (termed Bifactor models, i.e., models with two levels) (Jensen, 1998) underlie observable relationships among cognitive measures (Rijsdijk, Vernon, and Boomsma, 1998;Rijsdijk, Vernon, and Boomsma, 2002). Possible alternatives to a Bifactor structure are a Spearman model (General factor plus specifics) or a Thurstone model (group factors plus specifics) (see Jensen and Weng, 1994).…”

Section: Introductionmentioning

confidence: 99%

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Genetic and Environmental Sources of Covariance Between Reading Tests Used in Neuropsychological Assessment and IQ Subtests

et al. 2004

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In this study, we examined genetic and environmental influences on covariation among two reading tests used in neuropsychological assessment (Cambridge Contextual Reading Test [CCRT], [Beardsall, L., and Huppert, F. A. (1994 (Verbal, Performance, Reading). Reading performance was influenced by the genetic General factor (accounting for 13% and 20% of the variance for the CCRT and SGWRT, respectively), the genetic Verbal factor (explaining 17% and 19% of variance for the CCRT and SGWRT), and the genetic Reading factor (explaining 21% of the variance for both the CCRT and SGWRT). A common environment factor accounted for 25% and 14% of the CCRT and SGWRT variance, respectively. Genetic influences accounted for more than half of the phenotypic covariance between the reading tests and each of the IQ subtests. The heritabilities of the CCRT and SGWRT were 0.54 and 0.65, respectively. Observable covariance between reading assessments used by neuropsychologists to estimate IQ and IQ subtests appears to be largely due to genetic effects.

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Section: General Statistical Approach and Model Fittingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Genetic and Environmental Sources of Covariance Between Reading Tests Used in Neuropsychological Assessment and IQ Subtests

et al. 2004

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“…We computed g loadings from 9 WAIS subtests and individual g factor scores using a two-stage Schmid-Leiman hierarchical factor analyis (48), which has been recommended as the preferential method for extracting a g factor (49). In the original data matrix Z of 241 patients missing data were replaced by the mean.…”

Section: Methodsmentioning

confidence: 99%

Distributed neural system for general intelligence revealed by lesion mapping

Gläscher

Rudrauf

Colom

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

266

192

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General intelligence (g) captures the performance variance shared across cognitive tasks and correlates with real-world success. Yet it remains debated whether g reflects the combined performance of brain systems involved in these tasks or draws on specialized systems mediating their interactions. Here we investigated the neural substrates of g in 241 patients with focal brain damage using voxel-based lesion-symptom mapping. A hierarchical factor analysis across multiple cognitive tasks was used to derive a robust measure of g. Statistically significant associations were found between g and damage to a remarkably circumscribed albeit distributed network in frontal and parietal cortex, critically including white matter association tracts and frontopolar cortex. We suggest that general intelligence draws on connections between regions that integrate verbal, visuospatial, working memory, and executive processes.lesion patients | voxel-based lesion-symptom mapping | Wechsler Adult Intelligence Scale | white matter

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“…Thus, the OCQ taps nonverbal ability by testing knowledge about nonverbal topics. Together, this joint assessment of verbal and nonverbal abilities permits a reasonable estimate of the general factor (g) of intelligence (e.g., Jensen & Weng, 1994;Vernon, 1989).…”

Section: User Friendlinessmentioning

confidence: 99%

Measuring cognitive ability with the overclaiming technique

Paulhus

2004

Intelligence

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The overclaiming technique requires respondents to rate their familiarity with a list of general knowledge items (persons, places, things). Because 20% of the items are foils (i.e., do not exist), the response pattern can be analyzed with signal detection methods to yield the accuracy and bias scores for each respondent. In Study 1, the accuracy index showed strong associations with two standard IQ tests (β = .50-.59). Study 2 replicated the validity of the accuracy index with IQ and showed coherent associations with school grades, peer ratings, and self-ratings. Study 3 ensured that the validity of the accuracy index is invulnerable to a warning about foils. Study 4 showed that validity is maintained even when the ratings are completed at home. The discussion focuses on the advantages of this self-report approach over standard ability tests, namely, minimal stress, lack of time limit, or need for supervision, and flexibility of content.

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What is a good g?

Cited by 248 publications

References 29 publications

Genetic and Environmental Sources of Covariance Between Reading Tests Used in Neuropsychological Assessment and IQ Subtests

Genetic and Environmental Sources of Covariance Between Reading Tests Used in Neuropsychological Assessment and IQ Subtests

Distributed neural system for general intelligence revealed by lesion mapping

Measuring cognitive ability with the overclaiming technique

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