期刊
BIOMETRIKA
卷 105, 期 1, 页码 239-246出版社
OXFORD UNIV PRESS
DOI: 10.1093/biomet/asx076
关键词
Edgington's method; Fisher's method; George's method; Meta-analysis; Pearson's method; Stouffer's method; Tippett's method
资金
- Heilbronn Institute for Mathematical Research
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.
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