A comparison of combined p-value functions for meta-analysis
Year: 2025
Type: article
Abstract: P-value functions are modern statistical tools that unify effect estimation and hypothesis testing and can provide alternative point and interval estimates compared to standard meta-analysis methods, using any of the many p-value combination procedures available (Xie et al., 2011, JASA). We provide a systematic comparison of different combination procedures, both from a theoretical perspective and through simulation. We show that many prominent p-value combination methods (e.g. Fisher’s method) are not invariant to the orientation of the underlying one-sided p-values. Only Edgington’s method, a lesser-known combination method based on the sum of p-values, is orientation-invariant and still provides confidence intervals not restricted to be symmetric around the point estimate. Adjustments for heterogeneity can also be made and results from a simulation study indicate that Edgington’s method can compete with more standard meta-analytic methods.
DOI: 10.5167/uzh-281951
Authors: Held, Leonhard, Hofmann, Felix, Pawel, Samuel
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7124752719
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