A synthetic validity approach to testing differential prediction hypotheses
成果类型：
Article
署名作者：
Johnson, JW; Carter, GW; Davison, HK; Oliver, DH
刊物名称：
JOURNAL OF APPLIED PSYCHOLOGY
ISSN/ISSBN：
0021-9010
DOI：
10.1037//0021-9010.86.4.774
发表日期：
2001
页码：
774-780
关键词：
摘要：
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.
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