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p-Value Histograms: Inference and Diagnostics
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, tha...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164648/ https://www.ncbi.nlm.nih.gov/pubmed/30200313 http://dx.doi.org/10.3390/ht7030023 |
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author | Breheny, Patrick Stromberg, Arnold Lambert, Joshua |
author_facet | Breheny, Patrick Stromberg, Arnold Lambert, Joshua |
author_sort | Breheny, Patrick |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6164648 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-61646482018-10-11 p-Value Histograms: Inference and Diagnostics Breheny, Patrick Stromberg, Arnold Lambert, Joshua High Throughput Article 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. MDPI 2018-08-31 /pmc/articles/PMC6164648/ /pubmed/30200313 http://dx.doi.org/10.3390/ht7030023 Text en © 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/). |
spellingShingle | Article Breheny, Patrick Stromberg, Arnold Lambert, Joshua p-Value Histograms: Inference and Diagnostics |
title | p-Value Histograms: Inference and Diagnostics |
title_full | p-Value Histograms: Inference and Diagnostics |
title_fullStr | p-Value Histograms: Inference and Diagnostics |
title_full_unstemmed | p-Value Histograms: Inference and Diagnostics |
title_short | p-Value Histograms: Inference and Diagnostics |
title_sort | p-value histograms: inference and diagnostics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164648/ https://www.ncbi.nlm.nih.gov/pubmed/30200313 http://dx.doi.org/10.3390/ht7030023 |
work_keys_str_mv | AT brehenypatrick pvaluehistogramsinferenceanddiagnostics AT strombergarnold pvaluehistogramsinferenceanddiagnostics AT lambertjoshua pvaluehistogramsinferenceanddiagnostics |