title: A synthetic validity approach to testing differential prediction hypotheses.
abstract: A new method is presented for conducting differential prediction analyses that makes it possible to test differential prediction hypotheses with adequate statistical power even when the sample size within a job or a job family is very small. This method, called synthetic differential prediction analysis, represents an application of the logic of synthetic validation to differential prediction analyses. The authors explain this new method and describe its application in a selection-system validation study conducted in a large organization.
authors.affiliation: Personnel Decisions Research Institutes, Minneapolis, Minnesota 55414, USA. jeff.johnson@personneldecisions.com
authors.forename: J W
authors.initials: JW
authors.lastname: Johnson
authors.forename: G W
authors.initials: GW
authors.lastname: Carter
authors.forename: H K
authors.initials: HK
authors.lastname: Davison
authors.forename: D H
authors.initials: DH
authors.lastname: Oliver
mesh_terms: D003657:Decision Making; D005544:Forecasting; D006801:Humans; D008962:Models, Theoretical; D011590:Psychology, Industrial / Q000706:statistics & numerical data*