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  • 标题:idem: An R Package for Inferences in Clinical Trials with Death and Missingness
  • 本地全文:下载
  • 作者:Chenguang Wang ; Elizabeth Colantuoni ; Andrew Leroux
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2020
  • 卷号:93
  • 期号:1
  • 页码:1-35
  • DOI:10.18637/jss.v093.i12
  • 出版社:University of California, Los Angeles
  • 摘要:In randomized controlled trials of seriously ill patients, death is common and often defined as the primary endpoint. Increasingly, non-mortality outcomes such as functional outcomes are co-primary or secondary endpoints. Functional outcomes are not defined for patients who die, referred to as "truncation due to death", and among survivors, functional outcomes are often unobserved due to missed clinic visits or loss to follow-up. It is well known that if the functional outcomes "truncated due to death" or missing are handled inappropriately, treatment effect estimation can be biased. In this paper, we describe the package idem that implements a procedure for comparing treatments that is based on a composite endpoint of mortality and the functional outcome among survivors. Among survivors, the procedure incorporates a missing data imputation procedure with a sensitivity analysis strategy. A web-based graphical user interface is provided in the idem package to facilitate users conducting the proposed analysis in an interactive and user-friendly manner. We demonstrate idem using data from a recent trial of sedation interruption among mechanically ventilated patients.
  • 关键词:clinical trial;truncation due to death;composite endpoint;imputation;missing data;R;SACE;sensitivity analysis;shiny;Stan.
  • 其他关键词:clinical trial;composite endpoint;imputation;missing data;R;SACE;sensitivity analysis;shiny;Stan
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