Causal analysis of ordinal treatments and binary outcomes under truncation by death

• 成果类型: Article
• 署名作者: Wang, Linbo; Richardson, Thomas S.; Zhou, Xiao-Hua
• 署名单位: University of Washington; University of Washington Seattle; US Department of Veterans Affairs; Veterans Health Administration (VHA); Vet Affairs Puget Sound Health Care System
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/rssb.12188
• 发表日期: 2017
• 页码: 719-735
• 关键词: principal stratification; SOUTH-AFRICA; end-points; VIRAL LOAD; vaccine; inference; trials; randomization; incentives; mortality

摘要

It is common that, in multiarm randomized trials, the outcome of interest is truncated by death', meaning that it is only observed or well-defined conditioning on an intermediate outcome. In this case, in addition to pairwise contrasts, the joint inference for all treatment arms is also of interest. Under a monotonicity assumption we present methods for both pairwise and joint causal analyses of ordinal treatments and binary outcomes in the presence of truncation by death. We illustrate via examples the appropriateness of our assumptions in different scientific contexts.