非依从性随机试验中的单调工具变量

Y. Chiba
{"title":"非依从性随机试验中的单调工具变量","authors":"Y. Chiba","doi":"10.5691/JJB.31.93","DOIUrl":null,"url":null,"abstract":"Noncompliance is an important problem in randomized trials. The estimation and bounds of average causal effects (ACEs) have been discussed as a way to address this issue. Previous studies have considered ACEs under the instrumental variable (IV) assumption, which postulates that potential outcomes are constant across subject sub-populations assigned to separate treatment regimens. However, the IV assumption may not be valid in unmasked trials. In the present analyses, the IV assumption is relaxed to the monotone IV (MIV) assumption, which replaces equality in the IV assumption with inequality. We propose bounds on ACEs under the MIV assumption in addition to the other existing assumptions. The results demonstrate that the intention-to-treat effect is an upper or lower bound under one assumption and the per-protocol effect is an upper or lower bound under the other assumption, even using the MIV assumption in place of the IV assumption. These proposed bounds are illustrated using a classic randomized trial.","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2010-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The Monotone Instrumental Variable in Randomized Trials with Noncompliance\",\"authors\":\"Y. Chiba\",\"doi\":\"10.5691/JJB.31.93\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Noncompliance is an important problem in randomized trials. The estimation and bounds of average causal effects (ACEs) have been discussed as a way to address this issue. Previous studies have considered ACEs under the instrumental variable (IV) assumption, which postulates that potential outcomes are constant across subject sub-populations assigned to separate treatment regimens. However, the IV assumption may not be valid in unmasked trials. In the present analyses, the IV assumption is relaxed to the monotone IV (MIV) assumption, which replaces equality in the IV assumption with inequality. We propose bounds on ACEs under the MIV assumption in addition to the other existing assumptions. The results demonstrate that the intention-to-treat effect is an upper or lower bound under one assumption and the per-protocol effect is an upper or lower bound under the other assumption, even using the MIV assumption in place of the IV assumption. These proposed bounds are illustrated using a classic randomized trial.\",\"PeriodicalId\":365545,\"journal\":{\"name\":\"Japanese journal of biometrics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Japanese journal of biometrics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5691/JJB.31.93\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Japanese journal of biometrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5691/JJB.31.93","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

不依从性是随机试验中的一个重要问题。为了解决这一问题,本文讨论了平均因果效应(ace)的估计和界限。先前的研究在工具变量(IV)假设下考虑了ace,该假设假设分配到不同治疗方案的受试者亚群的潜在结果是恒定的。然而,IV假设可能在非蒙面试验中无效。在本分析中,将IV假设放宽为单调IV (MIV)假设,用不等式代替IV假设中的相等。除了现有的假设外,我们还在MIV假设下提出了ace的界。结果表明,意向治疗效应在一种假设下是上界或下界,而协议效应在另一种假设下是上界或下界,即使使用MIV假设代替IV假设。这些建议的界限是用一个经典的随机试验来说明的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Monotone Instrumental Variable in Randomized Trials with Noncompliance
Noncompliance is an important problem in randomized trials. The estimation and bounds of average causal effects (ACEs) have been discussed as a way to address this issue. Previous studies have considered ACEs under the instrumental variable (IV) assumption, which postulates that potential outcomes are constant across subject sub-populations assigned to separate treatment regimens. However, the IV assumption may not be valid in unmasked trials. In the present analyses, the IV assumption is relaxed to the monotone IV (MIV) assumption, which replaces equality in the IV assumption with inequality. We propose bounds on ACEs under the MIV assumption in addition to the other existing assumptions. The results demonstrate that the intention-to-treat effect is an upper or lower bound under one assumption and the per-protocol effect is an upper or lower bound under the other assumption, even using the MIV assumption in place of the IV assumption. These proposed bounds are illustrated using a classic randomized trial.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信