Accession Number : ADA298740
Title : Developing New Test Selection and Weight Stabilization Techniques for Designing Classification Efficient Composites.
Descriptive Note : Final rept. Sep 91-Aug 93,
Corporate Author : GEORGE WASHINGTON UNIV WASHINGTON DC OFFICE OF SPONSORED RESEARCH
Personal Author(s) : Johnson, Cecil D. ; Zeldner, Joseph ; Scholarios, Dolores
PDF Url : ADA298740
Report Date : JUL 1995
Pagination or Media Count : 63
Abstract : The major goal of this research was to specify a classification-efficient methodology for the construction of assignment composites of optimally selected and weighted tests drawn from a single battery of ASVAB and experimental tests and targeting a job family. The experiments examine the effects of the number of tests included in a composite, using different figures of merit as the standard for the selection of tests for components and stabilizing test regression weights. The research approach adopted involves a simulation of the Army selection and classification process using Project A validity data. Comparisons of classification efficiency obtained under each experimental condition are reported in terms of mean predicted performance (MPP). Findings indicate that five-test composites, tailored to operational job families and selected by a predictive validity index to provide positive weights, can provide an acceptable approximation of the maximum obtainable MPP. (MM)
Descriptors : *PERSONNEL SELECTION, *APTITUDE TESTS, JOBS, ARMY PERSONNEL, PERFORMANCE(HUMAN), TEST METHODS, REGRESSION ANALYSIS, WEIGHTING FUNCTIONS, LEAST SQUARES METHOD, FIGURE OF MERIT, APTITUDES.
Subject Categories : Psychology
Personnel Management and Labor Relations
Distribution Statement : APPROVED FOR PUBLIC RELEASE