Preprint Article Version 1 This version is not peer-reviewed

P-Value Histograms: Inference and Diagnostic

Version 1 : Received: 30 July 2018 / Approved: 5 August 2018 / Online: 5 August 2018 (10:36:41 CEST)

A peer-reviewed article of this Preprint also exists.

Breheny, P.; Stromberg, A.; Lambert, J. p-Value Histograms: Inference and Diagnostics. High-Throughput 2018, 7, 23. Breheny, P.; Stromberg, A.; Lambert, J. p-Value Histograms: Inference and Diagnostics. High-Throughput 2018, 7, 23.

Journal reference: High-Throughput 2018, 7, 23
DOI: 10.3390/ht7030023

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 normal and abnormal, 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 abnormal-looking p-value histograms are provided and based on case studies involving real biological experiments.

Subject Areas

p-value; histogram; inference; diagnostic

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.

Leave a public comment
Send a private comment to the author(s)
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.