5 papers · 1 filter
A General Mixture Loss Function to Optimize a Personalized Predictive Model
Tatiana Krikella, Joel A. Dubin
Advances in precision medicine increasingly drive methodological innovation in health research. A key development is the use of personalized prediction models (PPMs), which are fit…
Dynamic Prediction of Joint Longitudinal-Survival Models Using a Similarity-Based Approach
Minzee Kim, Joel A. Dubin
Longitudinal and time-to-event data are often analyzed in biomarker research to study the association between the longitudinal biomarker measurements and the event-time outcome, in…
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…
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…
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…