Choosing between methods of combining $p$-values

N A Heard and P Rubin-Delanchy

Biometrika, 2018, vol. 105, issue 1, 239-246

Abstract: Summary Combining $p$-values from independent statistical tests is a popular approach to meta-analysis, particularly when the data underlying the tests are either no longer available or are difficult to combine. Numerous $p$-value combination methods appear in the literature, each with different statistical properties, yet often the final choice used in a meta-analysis can seem arbitrary, as if all effort has been expended in building the models that gave rise to the $p$-values. Birnbaum (1954) showed that any reasonable $p$-value combiner must be optimal against some alternative hypothesis. Starting from this perspective and recasting each method of combining $p$-values as a likelihood ratio test, we present theoretical results for some standard combiners that provide guidance on how a powerful combiner might be chosen in practice.

Keywords: Edgington’s method; Fisher’s method; George’s method; Meta-analysis; Pearson’s method; Stouffer’s method; Tippett’s method (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (11)

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