Planning a method for covariate adjustment in individually randomised trials: a practical guide.
Planning a method for covariate adjustment in individually randomised trials: a practical guide.
复制标题
DOI：
10.1186/s13063-022-06097-z
复制
发表时间：
2022-04-18
期刊：
影响因子：
2.5
通讯作者：
White, Ian R.
中科院分区：
文献类型：
--
作者：
Morris, Tim P.;Walker, A. Sarah;Williamson, Elizabeth J.;White, Ian R.
关键词：
长期以来，人们一直建议在验证性随机试验的分析中考虑基线协变量，主要的统计学理由是这会增加功效，并且当随机化方案平衡协变量时，允许有效估计实验误差。有多种方法可用于解释协变量，但不清楚如何选择。从撰写统计分析计划的角度来看，我们考虑如何在三种最有前途的广泛方法之间进行选择：直接调整，标准化和逆概率治疗加权。这三种方法在渐近有效性、错误指定协变量函数的效率损失和处理设计平衡方面是相似的。如果目标是边际被估量（例如，风险差异或生存差异），则应避免直接调整，因为它涉及拟合受收敛问题影响的非标准模型。融合最有可能与IPTW。IPTW使用的稳健标准误差在小样本量下是反保守的。所有方法都可以使用类似的方法来处理缺失的协变量数据。由于结果数据缺失，每种方法都有自己的方法来估计全随机人群的治疗效果。我们说明了一些问题，在重新分析GetTested，随机试验，旨在评估电子性传播感染检测和结果服务的有效性。没有一种方法总是最好的：选择将取决于审判背景。我们鼓励试验者更经常地考虑所有三种方法。在线版本包含补充材料，可在（10.1186/s13063-022-06097-z）上获得。
It has long been advised to account for baseline covariates in the analysis of confirmatory randomised trials, with the main statistical justifications being that this increases power and, when a randomisation scheme balanced covariates, permits a valid estimate of experimental error. There are various methods available to account for covariates but it is not clear how to choose among them. Taking the perspective of writing a statistical analysis plan, we consider how to choose between the three most promising broad approaches: direct adjustment, standardisation and inverse-probability-of-treatment weighting. The three approaches are similar in being asymptotically efficient, in losing efficiency with mis-specified covariate functions and in handling designed balance. If a marginal estimand is targeted (for example, a risk difference or survival difference), then direct adjustment should be avoided because it involves fitting non-standard models that are subject to convergence issues. Convergence is most likely with IPTW. Robust standard errors used by IPTW are anti-conservative at small sample sizes. All approaches can use similar methods to handle missing covariate data. With missing outcome data, each method has its own way to estimate a treatment effect in the all-randomised population. We illustrate some issues in a reanalysis of GetTested, a randomised trial designed to assess the effectiveness of an electonic sexually transmitted infection testing and results service. No single approach is always best: the choice will depend on the trial context. We encourage trialists to consider all three methods more routinely. The online version contains supplementary material available at (10.1186/s13063-022-06097-z).
登录
查看更多内容
影响因子：
2
作者：
Moore, K. L.;van der Laan, M. J.
通讯作者：
van der Laan, M. J.
影响因子：
2
作者：
Dahabreh, Issa J.;Robertson, Sarah E.;Hernan, Miguel A.
通讯作者：
Hernan, Miguel A.
影响因子：
5.7
作者：
MENG, XL
通讯作者：
MENG, XL
影响因子：
2
作者：
Heinze, G;Schemper, M
通讯作者：
Schemper, M
影响因子：
2
作者：
Colantuoni E;Rosenblum M
通讯作者：
Rosenblum M