File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1080/00031305.2020.1717621
- Scopus: eid_2-s2.0-85112334326
- WOS: WOS:000516678400001
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Reconnecting p-Value and Posterior Probability Under One- and Two-Sided Tests
Title | Reconnecting p-Value and Posterior Probability Under One- and Two-Sided Tests |
---|---|
Authors | |
Keywords | Clinical trial Hypothesis testing One-sided test Posterior probability p-Value |
Issue Date | 2021 |
Publisher | American Statistical Association. The Journal's web site is located at http://www.tandfonline.com/utas |
Citation | The American Statistician, 2021, v. 75 n. 3, p. 265-275 How to Cite? |
Abstract | As a convention, p-value is often computed in frequentist hypothesis testing and compared with the nominal significance level of 0.05 to determine whether or not to reject the null hypothesis. The smaller the p-value, the more significant the statistical test. Under noninformative prior distributions, we establish the equivalence relationship between the p-value and Bayesian posterior probability of the null hypothesis for one-sided tests and, more importantly, the equivalence between the p-value and a transformation of posterior probabilities of the hypotheses for two-sided tests. For two-sided hypothesis tests with a point null, we recast the problem as a combination of two one-sided hypotheses along the opposite directions and establish the notion of a “two-sided posterior probability,” which reconnects with the (two-sided) p-value. In contrast to the common belief, such an equivalence relationship renders p-value an explicit interpretation of how strong the data support the null. Extensive simulation studies are conducted to demonstrate the equivalence relationship between the p-value and Bayesian posterior probability. Contrary to broad criticisms on the use of p-value in evidence-based studies, we justify its utility and reclaim its importance from the Bayesian perspective. |
Persistent Identifier | http://hdl.handle.net/10722/288179 |
ISSN | 2023 Impact Factor: 1.8 2023 SCImago Journal Rankings: 0.675 |
ISI Accession Number ID |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | SHI, H | - |
dc.contributor.author | Yin, G | - |
dc.date.accessioned | 2020-10-05T12:09:02Z | - |
dc.date.available | 2020-10-05T12:09:02Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | The American Statistician, 2021, v. 75 n. 3, p. 265-275 | - |
dc.identifier.issn | 0003-1305 | - |
dc.identifier.uri | http://hdl.handle.net/10722/288179 | - |
dc.description.abstract | As a convention, p-value is often computed in frequentist hypothesis testing and compared with the nominal significance level of 0.05 to determine whether or not to reject the null hypothesis. The smaller the p-value, the more significant the statistical test. Under noninformative prior distributions, we establish the equivalence relationship between the p-value and Bayesian posterior probability of the null hypothesis for one-sided tests and, more importantly, the equivalence between the p-value and a transformation of posterior probabilities of the hypotheses for two-sided tests. For two-sided hypothesis tests with a point null, we recast the problem as a combination of two one-sided hypotheses along the opposite directions and establish the notion of a “two-sided posterior probability,” which reconnects with the (two-sided) p-value. In contrast to the common belief, such an equivalence relationship renders p-value an explicit interpretation of how strong the data support the null. Extensive simulation studies are conducted to demonstrate the equivalence relationship between the p-value and Bayesian posterior probability. Contrary to broad criticisms on the use of p-value in evidence-based studies, we justify its utility and reclaim its importance from the Bayesian perspective. | - |
dc.language | eng | - |
dc.publisher | American Statistical Association. The Journal's web site is located at http://www.tandfonline.com/utas | - |
dc.relation.ispartof | The American Statistician | - |
dc.subject | Clinical trial | - |
dc.subject | Hypothesis testing | - |
dc.subject | One-sided test | - |
dc.subject | Posterior probability | - |
dc.subject | p-Value | - |
dc.title | Reconnecting p-Value and Posterior Probability Under One- and Two-Sided Tests | - |
dc.type | Article | - |
dc.identifier.email | Yin, G: gyin@hku.hk | - |
dc.identifier.authority | Yin, G=rp00831 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1080/00031305.2020.1717621 | - |
dc.identifier.scopus | eid_2-s2.0-85112334326 | - |
dc.identifier.hkuros | 315654 | - |
dc.identifier.volume | 75 | - |
dc.identifier.issue | 3 | - |
dc.identifier.eissn | 1537-2731 | - |
dc.identifier.isi | WOS:000516678400001 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 0003-1305 | - |