P-Value histograms: Inference and diagnostics

Patrick Breheny; Arnold Stromberg; Joshua Lambert

doi:10.3390/HT7030023

P-Value histograms: Inference and diagnostics

Patrick Breheny, Arnold Stromberg, Joshua Lambert

Dr. Bing Zhang Department of Statistics

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

23 Scopus citations

Abstract

It is increasingly common for experiments in biology and medicine to involve large numbers of hypothesis tests. A natural graphical method for visualizing these tests is to construct a histogram from the p-values of these tests. In this article, we examine the shapes, both regular and irregular, that these histograms can take on, as well as present simple inferential procedures that help to interpret the shapes in terms of diagnosing potential problems with the experiment. We examine potential causes of these problems in detail, and discuss potential remedies. Throughout, examples of irregular-looking p-value histograms are provided and based on case studies involving real biological experiments.

Original language	English
Article number	23
Journal	High-Throughput
Volume	7
Issue number	3
DOIs	https://doi.org/10.3390/HT7030023
State	Published - Sep 2018

Bibliographical note

Publisher Copyright:
© 2018 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

Diagnostics
Histograms
Inference
P-value

ASJC Scopus subject areas

Biotechnology
Bioengineering
Biochemistry
Biomedical Engineering

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10.3390/HT7030023

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P-Value histograms: Inference and diagnostics

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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