{"title":"了解 p 值和显著性。","authors":"Naomi Altman, Martin Krzywinski","doi":"10.1177/00236772241247106","DOIUrl":null,"url":null,"abstract":"<p><p><i>P-</i>values combined with estimates of effect size are used to assess the importance of experimental results. However, their interpretation can be invalidated by selection bias when testing multiple hypotheses, fitting multiple models or even informally selecting results that seem interesting after observing the data. We offer an introduction to principled uses of <i>p</i>-values (targeted at the non-specialist) and identify questionable practices to be avoided.</p>","PeriodicalId":18013,"journal":{"name":"Laboratory Animals","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Understanding <i>p</i>-values and significance.\",\"authors\":\"Naomi Altman, Martin Krzywinski\",\"doi\":\"10.1177/00236772241247106\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><i>P-</i>values combined with estimates of effect size are used to assess the importance of experimental results. However, their interpretation can be invalidated by selection bias when testing multiple hypotheses, fitting multiple models or even informally selecting results that seem interesting after observing the data. We offer an introduction to principled uses of <i>p</i>-values (targeted at the non-specialist) and identify questionable practices to be avoided.</p>\",\"PeriodicalId\":18013,\"journal\":{\"name\":\"Laboratory Animals\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Laboratory Animals\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/00236772241247106\",\"RegionNum\":4,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/9/24 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"VETERINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Laboratory Animals","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/00236772241247106","RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/9/24 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"VETERINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
摘要
P 值与效应大小估计值相结合,用于评估实验结果的重要性。然而,在测试多个假设、拟合多个模型或甚至在观察数据后非正式地选择看起来有趣的结果时,其解释可能会因选择偏差而失效。我们将介绍 p 值的原则性用法(针对非专业人士),并指出应避免的可疑做法。
P-values combined with estimates of effect size are used to assess the importance of experimental results. However, their interpretation can be invalidated by selection bias when testing multiple hypotheses, fitting multiple models or even informally selecting results that seem interesting after observing the data. We offer an introduction to principled uses of p-values (targeted at the non-specialist) and identify questionable practices to be avoided.
期刊介绍:
The international journal of laboratory animal science and welfare, Laboratory Animals publishes peer-reviewed original papers and reviews on all aspects of the use of animals in biomedical research. The journal promotes improvements in the welfare or well-being of the animals used, it particularly focuses on research that reduces the number of animals used or which replaces animal models with in vitro alternatives.