A likelihood-based approach to P-value interpretation provided a novel, plausible, and clinically useful research study metric.

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Abstract

Interpretation of clinical research findings using the paradigm of null hypothesis significance testing has a number of limitations. These include arbitrary dichotomization of results, lack of incorporation of study power and prior probability, and the confusing use of conditional probability. This study aimed to describe a novel method of P-value interpretation that would address these limitations.

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Author and article information

Journal

Journal ID (iso-abbrev): J Clin Epidemiol

Title: Journal of clinical epidemiology

Publisher: Elsevier BV

ISSN (Electronic): 1878-5921

ISSN (Print): 0895-4356

Publication date (Electronic): Dec 2017

Volume: 92

Affiliations

[1 ] The Alfred Hospital, 55 Commercial Rd Prahran, Melbourne 3004, Australia. Electronic address: nicholasadams@hotmail.com.

[2 ] The Alfred Hospital, 55 Commercial Rd Prahran, Melbourne 3004, Australia.

Article

Publisher Item ID: S0895-4356(16)30572-8

DOI: 10.1016/j.jclinepi.2017.08.016

PubMed ID: 28919460

SO-VID: 56814b45-d555-4521-a871-a39121dbefe4

History

Keywords: Bayes' theorem,P-values,Significance testing

Data availability:

Keywords: Bayes' theorem, P-values, Significance testing

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