Related Experiment Video
Updated: Feb 22, 2026
Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
A likelihood-based approach to P-value interpretation provided a novel, plausible, and clinically useful research
Nicholas G Adams1, Gerard O'Reilly1
1The Alfred Hospital, 55 Commercial Rd Prahran, Melbourne 3004, Australia.
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.
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