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
Trans- 28 porting experimental results with entropy balancing.Statistics in Medicine, 40(19): 4310–4326, 2021
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Introduces a transportability-based approach to model population-level exposure effects as a function of effect modifier prevalences for heterogeneity analysis.
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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
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From Subgroups to Population Composition: A Transportability Approach to Effect Heterogeneity
Introduces a transportability-based approach to model population-level exposure effects as a function of effect modifier prevalences for heterogeneity analysis.