Meta-analysis and partial correlation coefficients: A matter of weights

Abstract

This study builds on the simulation framework of a recent paper by Stanley and Doucouliagos (Research Synthesis Methods 2023;14;515-519). S&D use simulations to make the argument that meta-analyses using partial correlation coefficients (PCCs) should employ a "suboptimal" estimator of the PCC standard error when constructing weights for fixed effect and random effects estimation. We address concerns that their simulations and subsequent recommendation may give meta-analysts a misleading impression. While the estimator they promote dominates the "correct" formula in their Monte Carlo framework, there are other estimators that perform even better. We conclude that more research is needed before best practice recommendations can be made for meta-analyses with PCCs.

Keywords: bias; mean squared errors; meta-analysis; partial correlation coefficients.