title: Differential prediction and the use of multiple predictors: the omitted variables problem.
abstract: Moderated regression is widely used to examine differential prediction by race or gender. When using multiple predictors in a selection system, guidance as to whether differential prediction analysis should be conducted on each predictor individually, or on the set of predictors in combination, is lacking. Analyzing predictors individually creates the possibility of an omitted variable problem. Army Project A data were used to examine differential prediction by race with the use of personality measures for 79 predictor-criterion combinations. Traditional analysis indicated predictive bias by intercept in 45 instances and by slope in 7 instances; the inclusion of an Armed Services Vocational Aptitude Battery general factor as an additional predictor changed the conclusion in 32 cases for the intercept and in 3 cases for the slope.
authors.affiliation: Dept of Psychology, University of Minnesota, Elliott Hall, 75 East River Road, Minneapolis, MN 55455, USA. psackett@tc.umn.edu
authors.forename: Paul R
authors.initials: PR
authors.lastname: Sackett
authors.forename: Roxanne M
authors.initials: RM
authors.lastname: Laczo
authors.forename: Zachary P
authors.initials: ZP
authors.lastname: Lippe
mesh_terms: D005544:Forecasting; D005783:Gender Identity; D006801:Humans; D010551:Personality; D044469:Racial Groups