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Johnson, Wendy; Deary, Ian J.; Bouchard, Thomas J., Jr. – Educational and Psychological Measurement, 2018
Most study samples show less variability in key variables than do their source populations due most often to indirect selection into study participation associated with a wide range of personal and circumstantial characteristics. Formulas exist to correct the distortions of population-level correlations created. Formula accuracy has been tested…
Descriptors: Correlation, Sampling, Statistical Distributions, Accuracy
Molenaar, Dylan; Dolan, Conor V.; van der Maas, Han L. J. – Structural Equation Modeling: A Multidisciplinary Journal, 2011
In this article we present factor models to test for ability differentiation. Ability differentiation predicts that the size of IQ subtest correlations decreases as a function of the general intelligence factor. In the Schmid-Leiman decomposition of the second-order factor model, we model differentiation by introducing heteroscedastic residuals,…
Descriptors: Factor Structure, Models, Intelligence Quotient, Correlation
Peer reviewedBurton, D. Bradley; And Others – Psychological Assessment, 1994
A maximum-likelihood confirmatory factor analysis was performed by applying LISREL VII to the Wechsler Adult Intelligence Scale-Revised results of a normal elderly sample of 225 adults. Results indicate that a three-factor model fits best across all sample combinations. A mild gender effect is discussed. (SLD)
Descriptors: Factor Structure, Intelligence Tests, Maximum Likelihood Statistics, Older Adults
Chastain, Robert L.; Willson, Victor L. – 1986
Generalizability theory is based upon analysis of variance (ANOVA) and requires estimation of variance components for the ANOVA design under consideration in order to compute either G (Generalizability) or D (Decision) coefficients. Estimation of variance components has a number of alternative methods available using SAS, BMDP, and ad hoc…
Descriptors: Analysis of Variance, Computer Software, Correlation, Estimation (Mathematics)

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