Journal article
Using Beta Coefficients to Impute Missing Correlations in Meta-Analysis Research: Reasons for Caution
Journal of applied psychology, Vol.103(6), pp.644-658
06/01/2018
DOI: 10.1037/apl0000293
PMID: 29369653
Abstract
Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated (rho)over-bar (mean population correlation) and SD rho (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating (rho)over-bar and even larger biases when estimating SD rho. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis.
Details
- Title: Subtitle
- Using Beta Coefficients to Impute Missing Correlations in Meta-Analysis Research: Reasons for Caution
- Creators
- Philip L. Roth - Clemson UniversityHuy Le - The University of Texas at San AntonioIn-Sue Oh - Temple UniversityChad H. Van Iddekinge - Florida State UniversityPhilip Bobko - Virginia Tech
- Resource Type
- Journal article
- Publication Details
- Journal of applied psychology, Vol.103(6), pp.644-658
- Publisher
- Amer Psychological Assoc
- DOI
- 10.1037/apl0000293
- PMID
- 29369653
- ISSN
- 0021-9010
- eISSN
- 1939-1854
- Number of pages
- 15
- Language
- English
- Date published
- 06/01/2018
- Academic Unit
- Management and Entrepreneurship
- Record Identifier
- 9984380483602771
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