32 citations · 115 across the 16 of their papers we have counts for
4 papers · 1 filter
Propensity Score Adapted Covariate Selection for Causal Inference
Kangjie Zhou, Jinzhu Jia
In this paper, we propose a propensity score adapted variable selection procedure to select covariates for inclusion in propensity score models, in order to eliminate confounding b…
Variance Reduction for Causal Inference
Kangjie Zhou, Jinzhu Jia
Propensity score methods have been shown to be powerful in obtaining efficient estimators of average treatment effect (ATE) from observational data, especially under the existence…
Main and Interaction Effects Selection for Quadratic Discriminant Analysis via Penalized Linear Regression
Deqiang Zheng, Jinzhu Jia, Xiangzhong Fang +1
Discriminant analysis is a useful classification method. Variable selection for discriminant analysis is becoming more and more im- portant in a high-dimensional setting. This pape…
Mixed and missing data: a unified treatment with latent graphical models
Xiao Li, Jinzhu Jia, Yuan Yao
We propose to learn latent graphical models when data have mixed variables and missing values. This model could be used for further data analysis, including regression, classificat…