Alternatives to the P value: connotations of significance

Alternatives to the P value: connotations of significance
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초록

The statistical significance of a clinical trial analysis result is determined by a mathematical calculation and probability based on null hypothesis significance testing. However, statistical significance does not always align with meaningful clinical effects; thus, assigning clinical relevance to statistical significance is unreasonable. A statistical result incorporating a clinically meaningful difference is a better approach to present statistical significance. Thus, the minimal clinically important difference (MCID), which requires integrating minimum clinically relevant changes from the early stages of research design, has been introduced. As a follow-up to the previous statistical round article on P values, confidence intervals, and effect sizes, in this article, we present hands-on examples of MCID and various effect sizes and discuss the terms statistical significance and clinical relevance, including cautions regarding their use.

키워드

Clinical relevanceClinical significanceConfidence intervalsEffect sizeMinimal clinically important differencePatient outcome assessmentP valueStatistical significanceStatistics.CLINICALLY IMPORTANT DIFFERENCEEFFECT SIZE STATISTICSPAINOUTCOMES
제목
Alternatives to the P value: connotations of significance
제목 (타언어)
Alternatives to the P value: connotations of significance
저자
인준용Lee Dong Kyu
DOI
10.4097/kja.23630
발행일
2024-06
유형
Article
저널명
Korean Journal of Anesthesiology
77
3
페이지
316 ~ 325