Implications of the multidimensional nature of job performance for the validity of selection tests: Multivariate frameworks for studying test validity

Although most studies of criterion-related validity focus on univariate relationships, the complex and multidimensional nature of the performance construct and the widespread use of multiple selection devices argue in favor of multivariate frameworks for evaluating validity. Using a Monte Carlo simulation we estimated the validity of general cognitive ability tests and personality tests in predicting "job performance," where performance is conceptualized as a composite of multiple performance measures (i.e., individual job task performance and organizational citizenship behaviors). The validity of a selection battery varies substantially as a function of the relative weight given to both predictors and criteria; the 95% confidence interval for validities ranged from .20 to .78. The effective weights given to performance dimensions accounted for 34% of the variance in selection battery validities; depending on precisely how "performance" is defined, the same test battery can have relatively high or relatively low levels of validity. Our model suggests that the way an organization defines job performance is a source of true and important variability in validities, and that the validity of selection tests for predicting complex performance criteria may show considerably less generalizability that current metaanalysis of univariate validities would suggest.