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On the uncertainty from the first-stage estimation of prognostic covariate adjustment in randomized controlled trials

随机对照试验中预后协变量调整的第一阶段估计不确定性

Prognostic covariate adjustment (PROCOVA) is a two-sample two-stage estimation method for covariate adjustment in randomized controlled trials. In the first stage, a prognostic score, defined as the conditional expectation of an outcome given covariates under the control treatment, is estimated using historical data. In the second stage, analysis of covariance with the estimated prognostic score and treatment assignment as explanatory variables is performed, and the average…

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Estimation of time-varying treatment effects using marginal structural models dependent on partial treatment history

基于部分处理历史的边际结构模型:时变处理效应估计

Inverse probability (IP) weighting of marginal structural models (MSMs) can provide consistent estimators of time-varying treatment effects under correct model specifications and identifiability assumptions, even in the presence of time-varying confounding. However, this method has two problems: (i) inefficiency due to IP-weights cumulating all time points and (ii) bias and inefficiency due to the MSM misspecification. To address these problems, we propose (i) new IP-weights…

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