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TWO PITFALLS IN ASSESSING FAIRNESS OF SELECTION TESTS USING THE REGRESSION MODEL
Author(s) -
SCHMIDT FRANK L.,
HUNTER JOHN E.
Publication year - 1982
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.1744-6570.1982.tb02212.x
Subject(s) - psychology , selection (genetic algorithm) , regression analysis , covariance , regression , test (biology) , statistics , analysis of covariance , econometrics , scaling , social psychology , artificial intelligence , mathematics , computer science , paleontology , geometry , psychoanalysis , biology
This note examines two potential pitfalls in applying the Cleary or regression model of test fairness. The first lies in a misinterpretation of significance tests on intercept differences which can result when the researcher is unaware of the properties of analysis of covariance tests for intercept differences and relies on computer printouts of regression equations. The second lies in the dependence of some tests for intercept differences on predictor scaling. Once aware of them, the researcher can avoid both these pitfalls.