Meta-analyses of partial correlations are biased: Detection and solutions

T. Stanley, Chris Doucouliagos and Tomas Havranek

EconStor Preprints from ZBW - Leibniz Information Centre for Economics

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)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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https://www.econstor.eu/bitstream/10419/270940/1/pcc.pdf (application/pdf)

Related works:
Working Paper: Meta-Analyses of Partial Correlations Are Biased: Detection and Solutions (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:esprep:270940

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