Intercurrent events and estimands play a key role in defining the treatment effects of interest precisely. Sometimes the median or other quantiles of outcomes in a principal stratum according to potential occurrence of intercurrent events are of interest in randomized clinical trials. Naïve analyses such as those based on the observed occurrence of the intercurrent events lead to biased results. Therefore, we propose principal quantile treatment effect estimators that can nonparametrically estimate the distribution of potential outcomes by principal score weighting without relying on the exclusion restriction assumption. Our simulation studies show that the proposed method works in situations where the median or quantiles may be regarded as the preferred population‐level summary over the mean. We illustrate our proposed method by using data from a randomized controlled trial conducted on patients with nonerosive reflux disease.

中文翻译：

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使用主分数估计主分位数治疗效果


并发事件和估计值在精确定义感兴趣的治疗效果方面发挥着关键作用。有时，随机临床试验对主要层中根据并发事件的潜在发生情况的结果的中位数或其他分位数感兴趣。单纯的分析（例如基于观察到的并发事件发生的分析）会导致有偏差的结果。因此，我们提出了主分位数治疗效果估计器，它可以通过主分数加权非参数估计潜在结果的分布，而不依赖于排除限制假设。我们的模拟研究表明，所提出的方法适用于中位数或分位数可能被视为优于平均值的总体水平摘要的情况。我们通过使用对非糜烂性反流病患者进行的随机对照试验的数据来说明我们提出的方法。