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TEST VALIDATION FOR SCIENTIFIC UNDERSTANDING: TWO DEMONSTRATIONS OF AN APPROACH TO STUDYING PREDICTOR‐CRITERION LINKAGES
Author(s) -
PULAKOS ELAINE D.,
BORMAN WALTER C.,
HOUGH LEAETTA M.
Publication year - 1988
Publication title -
personnel psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.076
H-Index - 142
eISSN - 1744-6570
pISSN - 0031-5826
DOI - 10.1111/j.1744-6570.1988.tb00648.x
Subject(s) - psychology , construct (python library) , test (biology) , personality , construct validity , applied psychology , social psychology , big five personality traits , homogeneous , cognitive psychology , psychometrics , developmental psychology , computer science , paleontology , biology , programming language , physics , thermodynamics
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.