Range Restriction Corrections in Personnel Selection: A Mixed Range Restriction Correction Approach to Overcome a Key Limitation in Applying Case V

• 成果类型: Article
• 署名作者: Le, Huy; Oh, In-Sue; Roth, Philip L.; Schmidt, Frank L.
• 署名单位: University of Texas System; University of Texas at San Antonio; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University; Clemson University; University of Iowa
• 刊物名称: JOURNAL OF APPLIED PSYCHOLOGY
• ISSN/ISSBN: 0021-9010
• DOI: 10.1037/apl0001276
• 发表日期: 2025
• 页码: 1240-1263
• 关键词: range restriction; personnel selection; validity; validation; Meta-analysis

摘要

Recent advancements in range restriction (RR) correction research suggest that Case V (Dahlke & Wiernik, 2020; Le et al., 2016) is one of the most accurate approaches to correct for (indirect) RR. However, researchers have had difficulty applying the Case V approach, especially in validation and meta-analytic (including validity generalization) studies, because of the lack of information regarding one of its key components: the RR ratio of the criterion (u(Y)), particularly in the context of job performance ratings. In the present study, we provide a solution to this problem by presenting a mixed approach using Case IV to estimate the u(Y) of job performance ratings, a critical input in implementing Case V correction (by doing so, mixing Cases IV and V). The premise for this mixed approach hinges upon prior findings that Case IV yields the same unbiased estimates as does Case V as long as its full mediation assumption is met. The accuracy of the approach is then tested and compared to those of existing RR correction approaches (Cases II, IV, and V) using Monte Carlo simulations covering a wide range of conditions researchers may realistically encounter in their research. We discuss the present study's implications for personnel selection research and practice, along with study limitations and future research directions.