Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Click here for FREE ACCESS to this landmark database

Sign In to gain access to subscriptions and/or personal tools.
Theory & Psychology
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via ISI Web of Science (2)
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Hubbard, R.
Right arrow Articles by Lindsay, R. M.
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Why P Values Are Not a Useful Measure of Evidence in Statistical Significance Testing

Raymond Hubbard

DRAKE UNIVERSITY, Raymond.Hubbard{at}drake.edu

R. Murray Lindsay

UNIVERSITY OF LETHBRIDGE, m.lindsay{at}uleth.ca

Reporting p values from statistical significance tests is common in psychology's empirical literature. Sir Ronald Fisher saw the p value as playing a useful role in knowledge development by acting as an `objective' measure of inductive evidence against the null hypothesis. We review several reasons why the p value is an unobjective and inadequate measure of evidence when statistically testing hypotheses. A common theme throughout many of these reasons is that p values exaggerate the evidence against H0. This, in turn, calls into question the validity of much published work based on comparatively small, including .05, p values. Indeed, if researchers were fully informed about the limitations of the p value as a measure of evidence, this inferential index could not possibly enjoy its ongoing ubiquity. Replication with extension research focusing on sample statistics, effect sizes, and their confidence intervals is a better vehicle for reliable knowledge development than using p values. Fisher would also have agreed with the need for replication research.

Key Words: likelihood ratios • null hypothesis • (overlapping) confidence intervals • p values • posterior probabilities • replication

Theory & Psychology, Vol. 18, No. 1, 69-88 (2008)
DOI: 10.1177/0959354307086923
Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?


This article has been cited by other articles:


Home page
 Adv. Physiol. Educ.Home page
D. Curran-Everett
Explorations in statistics: hypothesis tests and P values
Advan Physiol Educ, June 1, 2009; 33(2): 81 - 86.
[Abstract] [Full Text] [PDF]