1 citations · 1 across the 4 of their papers we have counts for
4 papers
A New Covariate Selection Strategy for High Dimensional Data in Causal Effect Estimation with Multivariate Treatments
Juan Chen, Yingchun Zhou
Selection of covariates is crucial in the estimation of average treatment effects given observational data with high or even ultra-high dimensional pretreatment variables. Existing…
Weighted Euclidean balancing for a matrix exposure in estimating causal effect
Juan Chen, Yingchun Zhou
In many scientific fields such as biology, psychology and sociology, there is an increasing interest in estimating the causal effect of a matrix exposure on an outcome. Covariate b…
Causal Mediation Analysis with a Three-Dimensional Image Mediator
Minghao Chen, Yingchun Zhou
Causal mediation analysis is increasingly abundant in biology, psychology, and epidemiology studies, etc. In particular, with the advent of the big data era, the issue of high-dime…
Causal Effect Estimation for Multivariate Continuous Treatments
Juan Chen, Yingchun Zhou
Causal inference is widely used in various fields, such as biology, psychology and economics, etc. In observational studies, we need to balance the covariates before estimating cau…