G-computation of average treatment effects on the treated and the untreated

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• 作者：Aolin Wang ; Roch A. Nianogo ; Onyebuchi A. Arah
• 关键词：Average treatment effects on the treated (ATT) ; Average treatment effects on the untreated (ATU) ; G ; computation ; Parametric g ; formula ; Resampling ; Simulation
• 刊名：BMC Medical Research Methodology
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：17
• 期：1
• 全文大小：394KB
• 刊物主题：Theory of Medicine/Bioethics; Statistical Theory and Methods; Statistics for Life Sciences, Medicine, Health Sciences;
• 出版者：BioMed Central
• ISSN：1471-2288
• 卷排序：17

文摘

BackgroundAverage treatment effects on the treated (ATT) and the untreated (ATU) are useful when there is interest in: the evaluation of the effects of treatments or interventions on those who received them, the presence of treatment heterogeneity, or the projection of potential outcomes in a target (sub-) population. In this paper we illustrate the steps for estimating ATT and ATU using g-computation implemented via Monte Carlo simulation.