rpsftm: An R Package for Rank Preserving Structural Failure Time Models
rpsftm: An R Package for Rank Preserving Structural Failure Time Models
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DOI：
10.32614/rj-2017-068
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发表时间：
2017-12-01
期刊：
影响因子：
2.1
通讯作者：
Bond, Simon
中科院分区：
文献类型：
--
作者：
Allison, Annabel;White, Ian R.;Bond, Simon
在随机对照试验中，当参与者在研究期间从随机治疗转向其他试验治疗时，就会发生治疗转换。未能在分析中考虑治疗转换（即通过执行标准的意向治疗分析）可能导致对治疗疗效的估计有偏倚。保秩结构失效时间模型（RPSFTM）是一种在具有生存结局的试验中用于调整治疗转换的方法。RPSFTM是由Robins和Tsiatis（1991）提出的，并由White等人（1997,1999）发展而来。该方法基于随机化，仅使用随机化的治疗组、观察到的事件时间和治疗历史来估计因果治疗效果。治疗效果，Psi是通过平衡治疗组之间的反事实事件时间（如果没有接受治疗将观察到）来估计的。g估计用于找到y的值，使检验统计量Z (Psi) = 0。这通常是意向处理分析中使用的测试统计量，例如，日志等级测试统计量。我们提供了一个R包rpsftm来实现这个方法。
Treatment switching in a randomised controlled trial occurs when participants change from their randomised treatment to the other trial treatment during the study. Failure to account for treatment switching in the analysis (i.e. by performing a standard intention-to-treat analysis) can lead to biased estimates of treatment efficacy. The rank preserving structural failure time model (RPSFTM) is a method used to adjust for treatment switching in trials with survival outcomes. The RPSFTM is due to Robins and Tsiatis (1991) and has been developed by White et al. (1997, 1999).The method is randomisation based and uses only the randomised treatment group, observed event times, and treatment history in order to estimate a causal treatment effect. The treatment effect, Psi is estimated by balancing counter-factual event times (that would be observed if no treatment were received) between treatment groups. G-estimation is used to find the value of y such that a test statistic Z (Psi) = 0. This is usually the test statistic used in the intention-to-treat analysis, for example, the log rank test statistic.We present an R package, rpsftm, that implements the method.