| Abstract: | Prediction models employing multiple linear regression of raw scores, multiple linear regression of factor scores, the single best predictor, and a nine-point decision rule index were compared. The subjects were 296 clients undergoing vocational counseling and evaluation. Predictor variables included performance ratings, demographic variables, and WAIS subtest scores; the criterion was employment status upon program completion. The least statistically sophisticated model, employing the single best predictor, was the most successful approach. Considerable shrinkage in power of prediction was demonstrated upon cross-validation particularly for multiple linear regression of raw scores model, indicating the necessity of cross-validating prediction schemes. Additional suggestions are made to those designing prediction studies. |
