The adaptive calibration of testing p-values

Guimei Zhao, Xingzhong Xu and Li Wang

Communications in Statistics - Theory and Methods, 2016, vol. 45, issue 4, 922-932

Abstract: In statistical hypothesis testing, a p-value is expected to be distributed as the uniform distribution on the interval (0, 1) under the null hypothesis. However, some p-values, such as the generalized p-value and the posterior predictive p-value, cannot be assured of this property. In this paper, we propose an adaptive p-value calibration approach, and show that the calibrated p-value is asymptotically distributed as the uniform distribution. For Behrens–Fisher problem and goodness-of-fit test under a normal model, the calibrated p-values are constructed and their behavior is evaluated numerically. Simulations show that the calibrated p-values are superior than original ones.

Date: 2016
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DOI: 10.1080/03610926.2013.853791

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