[R-meta] random effects MA with correlations
fg@n@ng @ending from p@nteion@gr
Thu Sep 13 08:59:00 CEST 2018
Regarding the use of proper procedures to estimate between-study variance/heterogeneity (tau-squared) and its CIs, when performing random effects meta-analysis with correlation coefficients as effect sizes, using R, the "metafor" package implements REML by default when estimating tau-squared, while "metacor" uses DSL by default for examining random effects with correlation coefficients. Others suggest the Paule- Mandel method.
Thus, which is the optimal method in this case, especially when the number of studies= 20, the mean sample size=250, average r = 0.525 (95% CI= 0.411- 0.622), tau-squared= 0.10, I-squared= 98%, and correlations are converted to Fisher's z values? .
Moreover, is it necessary to apply the Hartung- Knapp method to adjust test statistics and CIs? Should we pay special attention to any "arguments" used in "metafor" package, when dealing with correlations?
Thanks in advance.
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