Imperial College London
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Professor Nick Heard

Faculty of Natural Sciences, Department of Mathematics

Chair in Statistics
 
 
 
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Contact

 

+44 (0)20 7594 1490n.heard Website

 
 
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Location

 

543Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Heard:2018:biomet/asx076,
author = {Heard, N and Rubin-Delanchy, P},
doi = {biomet/asx076},
journal = {Biometrika},
pages = {239--246},
title = {Choosing between methods of combining p-values},
url = {http://dx.doi.org/10.1093/biomet/asx076},
volume = {105},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Combining p-values from independent statistical tests is a popular approachto meta-analysis, particularly when the data underlying the tests are either nolonger available or are difficult to combine. A diverse range of p-valuecombination methods appear in the literature, each with different statisticalproperties. Yet all too often the final choice used in a meta-analysis canappear arbitrary, as if all effort has been expended building the models thatgave rise to the p-values. Birnbaum (1954) showed that any reasonable p-valuecombiner must be optimal against some alternative hypothesis. Starting fromthis perspective and recasting each method of combining p-values as alikelihood ratio test, we present theoretical results for some of the standardcombiners which provide guidance about how a powerful combiner might be chosenin practice.
AU  - Heard,N
AU  - Rubin-Delanchy,P
DO  - biomet/asx076
EP  - 246
PY  - 2018///
SN  - 0006-3444
SP  - 239
TI  - Choosing between methods of combining p-values
T2  - Biometrika
UR  - http://dx.doi.org/10.1093/biomet/asx076
UR  - http://arxiv.org/abs/1707.06897v4
UR  - http://hdl.handle.net/10044/1/55807
VL  - 105
ER  -
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