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ERIC Number: EJ1376273
Record Type: Journal
Publication Date: 2023-May
Pages: 5
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1759-2879
EISSN: EISSN-1759-2887
Correct Standard Errors Can Bias Meta-Analysis
Stanley, T. D.; Doucouliagos, Hristos
Research Synthesis Methods, v14 n3 p515-519 May 2023
Partial correlation coefficients are often used as effect sizes in the meta-analysis and systematic review of multiple regression analysis research results. There are two well-known formulas for the variance and thereby for the standard error (SE) of partial correlation coefficients (PCC). One is considered the "correct" variance in the sense that it better reflects the variation of the sampling distribution of partial correlation coefficients. The second is used to test whether the population PCC is zero, and it reproduces the test statistics and the p-values of the original multiple regression coefficient that PCC is meant to represent. Simulations show that the "correct" PCC variance causes random effects to be more biased than the alternative variance formula. Meta-analyses produced by this alternative formula statistically dominate those that use "correct" SEs. Meta-analysts should never use the "correct" formula for partial correlations' standard errors.
Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://bibliotheek.ehb.be:2191/en-us
Publication Type: Journal Articles; Information Analyses
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A