P-values: misunderstood and misused

P-values are widely used in both the social and natural sciences to quantify the statistical significance of observed results. The recent surge of big data research has made p-value an even more popular tool to test the significance of a study. However, substantial literature has been produced criti...

Full description

Bibliographic Details
Main Authors: Vidgen, B, Yasseri, T
Format: Journal article
Language:English
Published: Frontiers Media 2016
_version_ 1797111767226122240
author Vidgen, B
Yasseri, T
author_facet Vidgen, B
Yasseri, T
author_sort Vidgen, B
collection OXFORD
description P-values are widely used in both the social and natural sciences to quantify the statistical significance of observed results. The recent surge of big data research has made p-value an even more popular tool to test the significance of a study. However, substantial literature has been produced critiquing how p-values are used and understood. In this paper we review this recent critical literature, much of which is routed in the life sciences, and consider its implications for social scientific research. We provide a coherent picture of what the main criticisms are, and draw together and disambiguate common themes. In particular, we explain how the False Discovery Rate is calculated, and how this differs from a p-value. We also make explicit the Bayesian nature of many recent criticisms, a dimension that is often underplayed or ignored. We also identify practical steps to help remediate some of the concerns identified, and argue that p-values need to be contextualised within (i) the specific study, and (ii) the broader field of inquiry.
first_indexed 2024-03-07T08:15:00Z
format Journal article
id oxford-uuid:00c6e970-f969-4732-8887-74c6d21b063b
institution University of Oxford
language English
last_indexed 2024-03-07T08:15:00Z
publishDate 2016
publisher Frontiers Media
record_format dspace
spelling oxford-uuid:00c6e970-f969-4732-8887-74c6d21b063b2024-01-03T09:35:56ZP-values: misunderstood and misusedJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:00c6e970-f969-4732-8887-74c6d21b063bEnglishSymplectic Elements at OxfordFrontiers Media2016Vidgen, BYasseri, TP-values are widely used in both the social and natural sciences to quantify the statistical significance of observed results. The recent surge of big data research has made p-value an even more popular tool to test the significance of a study. However, substantial literature has been produced critiquing how p-values are used and understood. In this paper we review this recent critical literature, much of which is routed in the life sciences, and consider its implications for social scientific research. We provide a coherent picture of what the main criticisms are, and draw together and disambiguate common themes. In particular, we explain how the False Discovery Rate is calculated, and how this differs from a p-value. We also make explicit the Bayesian nature of many recent criticisms, a dimension that is often underplayed or ignored. We also identify practical steps to help remediate some of the concerns identified, and argue that p-values need to be contextualised within (i) the specific study, and (ii) the broader field of inquiry.
spellingShingle Vidgen, B
Yasseri, T
P-values: misunderstood and misused
title P-values: misunderstood and misused
title_full P-values: misunderstood and misused
title_fullStr P-values: misunderstood and misused
title_full_unstemmed P-values: misunderstood and misused
title_short P-values: misunderstood and misused
title_sort p values misunderstood and misused
work_keys_str_mv AT vidgenb pvaluesmisunderstoodandmisused
AT yasserit pvaluesmisunderstoodandmisused