Why<i>P</i>Values Are Not a Useful Measure of Evidence in Statistical Significance Testing
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- Raymond Hubbard
- DRAKE UNIVERSITY,
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- R. Murray Lindsay
- UNIVERSITY OF LETHBRIDGE,
Description
<jats:p>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 H<jats:sub>0</jats:sub>. 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.</jats:p>
Journal
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- Theory & Psychology
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Theory & Psychology 18 (1), 69-88, 2008-02
SAGE Publications
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Details 詳細情報について
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- CRID
- 1360855571426571904
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- ISSN
- 14617447
- 09593543
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- Data Source
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- Crossref