5 citations · 6 across the 10 of their papers we have counts for
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stat.ME2024
Causal Inference on Missing Exposure via Robust Estimation
Yuliang Shi, Yeying Zhu, Joel A. Dubin
How to deal with missing data in observational studies is a common concern for causal inference. When the covariates are missing at random (MAR), multiple approaches have been prov…
stat.ME2024
Model Selection for Causal Modeling in Missing Exposure Problems
Yuliang Shi, Yeying Zhu, Joel A. Dubin
In causal inference, properly selecting the propensity score (PS) model is an important topic and has been widely investigated in observational studies. There is also a large liter…
stat.ME2024★ 1 cited
A Personalized Predictive Model that Jointly Optimizes Discrimination and Calibration
Tatiana Krikella, Joel A. Dubin
Precision medicine is accelerating rapidly in the field of health research. This includes fitting predictive models for individual patients based on patient similarity in an attemp…