{"title":"P 值的替代方案:显著性的内涵。","authors":"Junyong In, Dong Kyu Lee","doi":"10.4097/kja.23630","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":17855,"journal":{"name":"Korean Journal of Anesthesiology","volume":"77 3","pages":"316-325"},"PeriodicalIF":4.2000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11150123/pdf/","citationCount":"0","resultStr":"{\"title\":\"Alternatives to the P value: connotations of significance.\",\"authors\":\"Junyong In, Dong Kyu Lee\",\"doi\":\"10.4097/kja.23630\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":17855,\"journal\":{\"name\":\"Korean Journal of Anesthesiology\",\"volume\":\"77 3\",\"pages\":\"316-325\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11150123/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Korean Journal of Anesthesiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.4097/kja.23630\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/4/29 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"ANESTHESIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Korean Journal of Anesthesiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4097/kja.23630","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/4/29 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"ANESTHESIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
临床试验分析结果的统计学意义是通过数学计算和基于零假设的概率显著性检验来确定的。然而,统计意义并不总是与有意义的临床效果相一致;因此,赋予统计意义以临床相关性是不合理的。包含临床意义差异的统计结果是呈现统计意义的更好方法。因此,引入了最小临床意义差异(MCID),要求在研究设计的早期阶段就纳入最小临床相关性变化。作为上一篇关于 P 值、置信区间和效应大小的统计综述文章的后续文章,我们将在本文中介绍 MCID 和各种效应大小的实例,并讨论统计学意义和临床相关性这两个术语,包括使用时的注意事项。
Alternatives to the P value: connotations of significance.
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.