{"title":"P值,功率和医学意义的可信结果。","authors":"A Indrayan","doi":"10.4103/jpgm.jpgm_30_25","DOIUrl":null,"url":null,"abstract":"<p><strong>Abstract: </strong>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.</p>","PeriodicalId":94105,"journal":{"name":"Journal of postgraduate medicine","volume":" ","pages":"91-94"},"PeriodicalIF":0.0000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12236413/pdf/","citationCount":"0","resultStr":"{\"title\":\"3. P values, power, and medical significance for credible results.\",\"authors\":\"A Indrayan\",\"doi\":\"10.4103/jpgm.jpgm_30_25\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Abstract: </strong>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.</p>\",\"PeriodicalId\":94105,\"journal\":{\"name\":\"Journal of postgraduate medicine\",\"volume\":\" \",\"pages\":\"91-94\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12236413/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of postgraduate medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4103/jpgm.jpgm_30_25\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/6/9 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of postgraduate medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4103/jpgm.jpgm_30_25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/6/9 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
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 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.