The Wechsler Adult Intelligence Scale (WAIS) has been widely used in research as well as clinical applications. But the conclusions about adult intelligence that can be drawn from the existing WAIS literature are often clouded and sometimes contradictory. WAIS summary data, subscale scores, item data and other information on over 50,000 individual subjects has been obtained from over 200 different experimental studies. Statistical stratification and crossvalidation procedures have been used to select specialized subsamples for analyses.
This research aims i s to define and isolate the growth curves of adult intelligence as measured by the WAIS. Large scale Longitudinal data (N=2,500) and family data (N=3,500) have already been collected from many diverse studies, and ranging over the entire adult age span. The larger sample of cross- sectional WAIS data (N=16,000) will be used to match individuals based on some crucial demographic characteristics. Statistical comparisons of the longitudinal, family, and cross-sectional WAIS data will be made to quantify test-retest and within-family selection effects. A variety of latent variable structural equation models (e.g., LISREL, etc.) will be used to examine the basic questions of factorial invariance over age and time. Growth curve models will be developed which will account for components of age, date of testing, education, and gender, as well as subject selectively and biases due to attrition. One aspect of this work will revolve around extensions of the latent growth model (LGM), especially for use with the analysis of incomplete growth curves, and other analyses will use graphical techniques. In a broad sense, we will adapt contemporary methods from human physical growth and epidemiology for use in psychological aging research.
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