Meta-Analyses of Partial Correlations Are Biased: Detection and Solutions

T. Stanley, Chris Doucouliagos and Tomas Havranek

No 2023/17, Working Papers IES from Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies

Abstract: We demonstrate that all meta-analyses of partial correlations are biased, and yet hundreds of meta-analyses of partial correlation coefficients (PCC) are conducted each year widely across economics, business, education, psychology, and medical research. To address these biases, we offer a new weighted average, UWLS+3. UWLS+3 is the unrestricted weighted least squares weighted average that makes an adjustment to the degrees of freedom that are used to calculate partial correlations and, by doing so, renders trivial any remaining meta-analysis bias. Our simulations also reveal that these meta-analysis biases are small-sample biases (n

Keywords: partial correlation coefficients; meta-analysis; bias; small sample (search for similar items in EconPapers)
JEL-codes: C83 (search for similar items in EconPapers)
Pages: 24 pages
Date: 2023-05, Revised 2023-05
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Related works:
Working Paper: Meta-analyses of partial correlations are biased: Detection and solutions (2023)
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