Causal inference with noisy data: Bias analysis and estimation approaches to simultaneously addressing missingness and misclassification in binary outcomes-论文-万方医学网

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Causal inference with noisy data: Bias analysis and estimation approaches to simultaneously addressing missingness and misclassification in binary outcomes

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第一作者： Di Shu

作者： Di Shu ^[1] ; Grace Y. Yi ^[2]

作者单位： Department of Population Medicine,Harvard Medical School and Harvard Pilgrim Health Care Institute ^[1] Department of Statistical and Actuarial Sciences,Department of Computer Science, University of ^[2]

关键词 causal inference double robustness inverse probability weighting misclassification missing data

发布时间 2022-06-23

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Causal inference with noisy data: Bias analysis and estimation approaches to simultaneously addressing missingness and misclassification in binary outcomes

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