Revival of Test Bias Research in Preemployment Testing

• 成果类型: Article
• 署名作者: Aguinis, Herman; Culpepper, Steven A.; Pierce, Charles A.
• 署名单位: Indiana University System; IU Kelley School of Business; Indiana University Bloomington; Children's Hospital Colorado; University of Colorado System; University of Colorado Denver; University of Colorado Anschutz Medical Campus; University of Memphis
• 刊物名称: JOURNAL OF APPLIED PSYCHOLOGY
• ISSN/ISSBN: 0021-9010
• DOI: 10.1037/a0018714
• 发表日期: 2010
• 页码: 648-680
• 关键词: selection fairness; testing practices; employee selection; human resource management; staffing

摘要

We developed a new analytic proof and conducted Monte Carlo simulations to assess the effects of methodological and statistical artifacts on the relative accuracy of intercept- and slope-based test bias assessment. The main simulation design included 3,185,000 unique combinations of a wide range of values for true intercept- and slope-based test bias, total sample size, proportion of minority group sample size to total sample size, predictor (i.e., preemployment test scores) and criterion (i.e., job performance) reliability, predictor range restriction, correlation between predictor scores and the dummy-coded grouping variable (e.g., ethnicity), and mean difference between predictor scores across groups. Results based on 15 billion 925 million individual samples of scores and more than 8 trillion 662 million individual scores raise questions about the established conclusion that test bias in preemployment testing is nonexistent and, if it exists, it only occurs regarding intercept-based differences that favor minority group members. Because of the prominence of test fairness in the popular media, legislation, and litigation, our results point to the need to revive test bias research in preemployment testing.