Test Validation for Scientific Understanding: Two Demonstrations of an Approach to Studying Predictor-Criterion Linkages

This paper argues that a construct‐oriented approach to test validation is likely to enhance scientific understanding of our predictor measures, performance criteria, and links between them. In particular, examining relationships between relatively homogeneous predictors and criteria tapping specific performance areas operationalizes earlier conceptual statements made by Guion and Dunnette about test validation for scientific understanding. Two demonstrations are offered to show how measures of predictor constructs have predictably different patterns of correlations with different criteria. In a study of Navy recruiters (N= 267), individual personality scales had significantly different relationships with three different rating criteria; in a second study, with Army enlisted soldiers (N= 8, 642), cognitive ability and personality construct measures also showed predictable patterns of correlations, with rating criteria measuring three different performance areas. The paper discusses scientific and practical implications of this construct‐oriented approach to test validation