New calibration weighting and control variate estimators for causal inference with multiple misclassified binary exposures achieve consistency and double robustness without modeling the misclassification process, with application showing 69% attenuation of Pseudomonas effect on FEV1 when using swabs
A framework for covariate balance using Bregman distances.Scandinavian Journal of Statistics, 48 (3):790–816, 2021
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Causal Inference with Multiple Misclassified Exposures: A Control Variate-Adjusted Calibration Weighting Approach
New calibration weighting and control variate estimators for causal inference with multiple misclassified binary exposures achieve consistency and double robustness without modeling the misclassification process, with application showing 69% attenuation of Pseudomonas effect on FEV1 when using swabs