Validation Is Like Motor Oil: Synthetic Is Better

Although synthetic validation has long been suggested as a practical and defensible approach to establishing validity evidence, synthetic validation techniques are infrequently used and not well understood by the practitioners and researchers they could most benefit. Therefore, we describe the assumptions, origins, and methods for establishing validity evidence of the two primary types of synthetic validation techniques: (a) job component validity and (b) job requirements matrix. We then present the case for synthetic validation as the best approach for many situations and address the potential limitations of synthetic validation. We conclude by proposing the development of a comprehensive database to build prediction equations for use in synthetic validation of jobs across the U.S. economy and reviewing potential obstacles to the creation of such a database. We maintain that synthetic validation is a practically useful methodology that has great potential to advance the science and practice of industrial and organizational psychology.

A Test of a Proposed Method for Estimating Validity of a Multivariate Composite Predictor: Extending the Job Component Validity Model

In this study, a proposed extension to the job component validity model from the Position Analysis Questionnaire was tested. Job component validity, a form of synthetic validation, allows researchers to select useful predictors and to estimate the criterion-related validity of tests based on conducting a job analysis which includes the Position Analysis Questionnaire. Morris and colleagues described a method for estimating the multiple correlation of a test battery assembled via job component validity estimates. In the current study, job component validity estimates, derived from the multiple correlation procedure proposed by Morris, et al., were compared to unit-weighted validity estimates obtained in a criterion-related validity study of six job progressions. The multivariate job component validity estimates were comparable to unit-weighted validity coefficients obtained using supervisory ratings as criteria. Multivariate job component validity estimates were conservative compared to corrected unit-weighted validity coefficients.