期刊论文详细信息
Journal of Causal Inference
Estimating Mann–Whitney-Type Causal Effects for Right-Censored Survival Outcomes
article
Zhiwei Zhang1  Chunling Liu2  Shujie Ma1  Min Zhang3 
[1] University of California, Department of Statistics, 900 University Ave, United States;Hong Kong Polytechnic University, Department of Applied Mathematics;University of Michigan, Department of Biostatistics, United States
关键词: confounding;    coarsening;    double robustness;    time to event;    treatment comparison;   
DOI  :  10.1515/jci-2018-0010
来源: De Gruyter
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【 摘 要 】

Mann–Whitney-type causal effects are clinically relevant, easy to interpret, and readily applicable to a wide range of study settings. This article considers estimation of such effects when the outcome variable is a survival time subject to right censoring. We derive and discuss several methods: an outcome regression method based on a regression model for the survival outcome, an inverse probability weighting method based on models for treatment assignment and censoring, and two doubly robust methods that involve both types of models and that remain valid under correct specification of the outcome model or the other two models. The methods are compared in a simulation study and applied to an observational study of hospitalized pneumonia.

【 授权许可】

CC BY   

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