Not Restricted to Selection Research: Accounting for Indirect Range Restriction in Organizational Research
meta-analysis, reliability and validity, construct validation procedures
Digital Object Identifier (DOI)
Range restriction is a common problem in organizational research and is an important statistical artifact to correct for in meta-analysis. Historically, researchers have had to rely on range-restriction corrections that only make use of range-restriction information for one variable, but it is not uncommon for researchers to have such information for both variables in a correlation (e.g., when studying the correlation between two predictor variables). Existing meta-analytic methods incorporating bivariate range-restriction corrections overlook their unique implications for estimating the sampling variance of corrected correlations and for accurately assigning weights to studies in individual-correction meta-analyses. We introduce new methods for computing individual-correction and artifact-distribution meta-analyses using the bivariate indirect range restriction (BVIRR; “Case V”) correction and describe improved methods for applying BVIRR corrections that substantially reduce bias in parameter estimation. We illustrate the effectiveness of these methods in a large-scale simulation and in meta-analyses of expatriate data. We provide R code to implement the methods described in this article; more comprehensive and robust functions for applying these methods are available in the psychmeta package for R.
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Citation / Publisher Attribution
Organizational Research Methods, v. 23, issue 4, p. 717-749
Scholar Commons Citation
Dahlke, Jeffrey A. and Wiernik, Brenton M., "Not Restricted to Selection Research: Accounting for Indirect Range Restriction in Organizational Research" (2019). Psychology Faculty Publications. 2456.