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Range restriction corrections in personnel selection: A mixed range restriction correction approach to overcome a key
Huy Le1, In-Sue Oh2, Philip L Roth3
1Department of Management, Alvarez College of Business, University of Texas at San Antonio.
Abstract:
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 (uY), 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 uY 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. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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