3. P values, power, and medical significance for credible results

ABSTRACT Type I and Type II errors are inherent in any empirical medical research on an antecedent-outcome relationship when it is based on a dataset of a sample of subjects. Type I error is the incorrect rejection of a true null hypothesis, and its probability in a study is the P value. This error...

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Bibliographic Details
Published inJournal of postgraduate medicine Vol. 71; no. 2; pp. 91 - 94
Main Author Indrayan, A
Format Journal Article
LanguageEnglish
Published India Wolters Kluwer - Medknow 01.04.2025
Medknow Publications & Media Pvt. Ltd
Edition2
Subjects
Biomedical Research - standards
Data Interpretation, Statistical
Humans
Probability
Research Design
Review (Medical Statistics)
Review Article (Medical Statistics)
Type-I and Type-II errors
P values
statistical significance
power
Medical significance
Online AccessGet full text
ISSN0022-3859
0972-2823
DOI10.4103/jpgm.jpgm_30_25

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Summary:ABSTRACT Type I and Type II errors are inherent in any empirical medical research on an antecedent-outcome relationship when it is based on a dataset of a sample of subjects. Type I error is the incorrect rejection of a true null hypothesis, and its probability in a study is the P value. This error is more serious and is kept under control by specifying a cap called the level of significance. The complement of the probability of Type II error, called power, is the probability of not missing a medically significant effect when present. This article concisely explains P values, power, and medical significance in nontechnical terms for our medical colleagues and their implications for assessing the credibility of medical research.
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ISSN:0022-3859
0972-2823
DOI:10.4103/jpgm.jpgm_30_25