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.
Document Type
Article
Publication Date
8-31-2018
Digital Object Identifier (DOI)
https://doi.org/10.3390/ht7030023
Repository Citation
Breheny, Patrick; Stromberg, Arnold; and Lambert, Joshua, "p-Value Histograms: Inference and Diagnostics" (2018). Statistics Faculty Publications. 24.
https://uknowledge.uky.edu/statistics_facpub/24
Notes/Citation Information
Published in High-Throughput, v. 7, issue 3, 23, p. 1-13.
© 2018 by the authors. Licensee MDPI, Basel, Switzerland.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).