{"title":"随机试验中的意向治疗比较","authors":"R. Prentice, A. Aragaki","doi":"10.1214/21-sts830","DOIUrl":null,"url":null,"abstract":"Intention-to-treat (ITT) comparisons have a central place in reporting on randomized controlled trials, though there are typically additional analyses of interest such as those making adjustments for nonadherence. In our ITT reporting of results from the Women’s Health Initiative (WHI) randomized trials we have relied primarily on highly flexible hazard ratio (Cox) regression methods. However, these methods, especially the proportional hazards special case, have been criticized for being difficult to interpret and frequently oversimplified, and for not being consistent with modern causality theories using potential outcomes. Here we address these topics and extend our use of hazard rate methods for ITT comparisons in the WHI trials.","PeriodicalId":51172,"journal":{"name":"Statistical Science","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Intention-to-Treat Comparisons in Randomized Trials\",\"authors\":\"R. Prentice, A. Aragaki\",\"doi\":\"10.1214/21-sts830\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Intention-to-treat (ITT) comparisons have a central place in reporting on randomized controlled trials, though there are typically additional analyses of interest such as those making adjustments for nonadherence. In our ITT reporting of results from the Women’s Health Initiative (WHI) randomized trials we have relied primarily on highly flexible hazard ratio (Cox) regression methods. However, these methods, especially the proportional hazards special case, have been criticized for being difficult to interpret and frequently oversimplified, and for not being consistent with modern causality theories using potential outcomes. Here we address these topics and extend our use of hazard rate methods for ITT comparisons in the WHI trials.\",\"PeriodicalId\":51172,\"journal\":{\"name\":\"Statistical Science\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2022-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistical Science\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1214/21-sts830\",\"RegionNum\":1,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistical Science","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1214/21-sts830","RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Intention-to-Treat Comparisons in Randomized Trials
Intention-to-treat (ITT) comparisons have a central place in reporting on randomized controlled trials, though there are typically additional analyses of interest such as those making adjustments for nonadherence. In our ITT reporting of results from the Women’s Health Initiative (WHI) randomized trials we have relied primarily on highly flexible hazard ratio (Cox) regression methods. However, these methods, especially the proportional hazards special case, have been criticized for being difficult to interpret and frequently oversimplified, and for not being consistent with modern causality theories using potential outcomes. Here we address these topics and extend our use of hazard rate methods for ITT comparisons in the WHI trials.
期刊介绍:
The central purpose of Statistical Science is to convey the richness, breadth and unity of the field by presenting the full range of contemporary statistical thought at a moderate technical level, accessible to the wide community of practitioners, researchers and students of statistics and probability.