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Peer reviewed Peer reviewed
Zajonc, R. B.; And Others – American Sociological Review, 1991
Responds to "Birth Order and Intelligence: Further Tests of the Confluence Model" by Robert D. Retherford and William H. Sewell. Reviews their arguments and suggests that their analyses of the Wisconsin Longitudinal Study data support rather than contradict the model. (CJS)
Descriptors: Birth Order, Intelligence Differences, Longitudinal Studies, Mathematical Models
Peer reviewed Peer reviewed
Milkman, Roger – Journal of Educational Statistics, 1978
Sets of randomly generated numbers are used to produce simulated data sets to illustrate that high heritability of a property within each of two populations may be consistent with a vanishingly small heritability in the combined population. (A response by Jensen appears in the next issue of Journal of Educational Statistics, p.385). (CTM)
Descriptors: Analysis of Variance, Heredity, Intelligence Differences, Mathematical Models
Peer reviewed Peer reviewed
Whitely, Susan E. – Intelligence, 1980
This article examines the potential contribution of latent trait models to the study of intelligence. Nontechnical introductions to both unidimensional and multidimensional latent trait models are given. Multidimensional latent trait models can be used to test alternative multiple component theories of test item processing. (Author/CTM)
Descriptors: Ability, Aptitude Tests, Cognitive Processes, Intelligence
Peer reviewed Peer reviewed
Retherford, Robert D.; Sewell, William H. – American Sociological Review, 1991
Confluence theory was developed to explain the negative effects of birth order on intelligence. Using aggregate, between-family, within-family, and paired-sibling data from the Wisconsin Longitudinal Study, tests the mathematical form of confluence theory and finds no support for it. Suggests that statistical methods used to fit the model to the…
Descriptors: Birth Order, Goodness of Fit, Intelligence Differences, Intelligence Quotient
Bond, Lloyd – New Directions for Testing and Measurement, 1981
While some forms of test bias (for example, bias in selection and prediction) appear amenable to definitional consensus, a definition of cultural bias will remain problematic so long as it is confused with the nature/nurture issue. (Author/BW)
Descriptors: Cultural Differences, Evaluation Criteria, Experimenter Characteristics, Intelligence Differences