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

Abstract:

OBJECTIVES: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. STUDY DESIGN AND SETTING:Published clinical research was reinterpreted using the delta likelihood ratio. The delta likelihood ratio is an application of Bayes' rule incorporating the P-value and study power. Calculation of the delta likelihood ratio allows the determination of the most likely effect size using the maximum likelihood principle. RESULTS:We showed that the delta likelihood is easily calculated and produces plausible results using the example of several previously published research studies. Empirical evidence of validity was demonstrated by simulation. CONCLUSION:The delta likelihood ratio and most likely effect size are simple and intuitive metrics to summarize research findings. The delta likelihood ratio incorporates study power and provides a continuous measure of the probability that the research result is a true effect. The most likely effect size is an easily understood metric that should aid the interpretation of research.

journal_name

J Clin Epidemiol

authors

Adams NG,O'Reilly G

doi

10.1016/j.jclinepi.2017.08.016

subject

Has Abstract

pub_date

2017-12-01 00:00:00

pages

111-115

eissn

0895-4356

issn

1878-5921

pii

S0895-4356(16)30572-8

journal_volume

92

pub_type

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