Combining p-values using order-based methods

Ori Davidov

doi:10.1016/j.csda.2011.01.024

Combining p-values using order-based methods

Ori Davidov

Department of Statistics

University of Haifa

Research output: Contribution to journal › Article › peer-review

Abstract

Statistical practice often requires combining evidence from independent sources. A popular approach is to combine p-values. Motivated by the observation that p-values under the alternative are stochastically smaller than p-values under the null, we develop new combination rules that explicitly account for this ordering. The new combination rules are broadly applicable, optimal against some alternatives, and highly efficient against optimal procedures.

Original language	American English
Pages (from-to)	2433-2444
Number of pages	12
Journal	Computational Statistics and Data Analysis
Volume	55
Issue number	7
DOIs	https://doi.org/10.1016/j.csda.2011.01.024
State	Published - 1 Jul 2011

Keywords

Combining functions
Optimality
Restricted inference
Stochastic order relations
Testing uniformity
p-values

All Science Journal Classification (ASJC) codes

Statistics and Probability
Computational Mathematics
Computational Theory and Mathematics
Applied Mathematics

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10.1016/j.csda.2011.01.024

Cite this

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abstract = "Statistical practice often requires combining evidence from independent sources. A popular approach is to combine p-values. Motivated by the observation that p-values under the alternative are stochastically smaller than p-values under the null, we develop new combination rules that explicitly account for this ordering. The new combination rules are broadly applicable, optimal against some alternatives, and highly efficient against optimal procedures.",

keywords = "Combining functions, Optimality, Restricted inference, Stochastic order relations, Testing uniformity, p-values",

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AB - Statistical practice often requires combining evidence from independent sources. A popular approach is to combine p-values. Motivated by the observation that p-values under the alternative are stochastically smaller than p-values under the null, we develop new combination rules that explicitly account for this ordering. The new combination rules are broadly applicable, optimal against some alternatives, and highly efficient against optimal procedures.

KW - Combining functions

KW - Optimality

KW - Restricted inference

KW - Stochastic order relations

KW - Testing uniformity

KW - p-values

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JO - Computational Statistics and Data Analysis

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IS - 7

ER -

Combining p-values using order-based methods

Abstract

Keywords

All Science Journal Classification (ASJC) codes

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