activity
20182022
most citedBayesian Sparse Mediation Analysis with Targeted Penalization of Natural Indirect Effects

4 citations · 8 across the 4 of their papers we have counts for

collaborators

6 papers

stat.ME20221 cited

Methods for Large-scale Single Mediator Hypothesis Testing: Possible Choices and Comparisons

Jiacong Du, Xiang Zhou, Wei Hao +3

Mediation hypothesis testing for a large number of mediators is challenging due to the composite structure of the null hypothesis, H0:alpha*beta=0 (alpha: effect of the exposure on…

stat.ME20202 cited

Some Doubly and Multiply Robust Estimators of Controlled Direct Effects

Xiang Zhou

This letter introduces several doubly, triply, and quadruply robust estimators of the controlled direct effect. Among them, the triply and quadruply robust estimators are locally s…

stat.AP20201 cited

Bayesian Hierarchical Models for High-Dimensional Mediation Analysis with Coordinated Selection of Correlated Mediators

Yanyi Song, Xiang Zhou, Jian Kang +9

We consider Bayesian high-dimensional mediation analysis to identify among a large set of correlated potential mediators the active ones that mediate the effect from an exposure va…

stat.AP20204 cited

Bayesian Sparse Mediation Analysis with Targeted Penalization of Natural Indirect Effects

Yanyi Song, Xiang Zhou, Jian Kang +9

Causal mediation analysis aims to characterize an exposure's effect on an outcome and quantify the indirect effect that acts through a given mediator or a group of mediators of int…

stat.AP2018

Regression-with-residuals Estimation of Marginal Effects: A Method of Adjusting for Treatment-induced Confounders that may also be Moderators

Geoffrey T. Wodtke, Zahide Alaca, Xiang Zhou

Treatment-induced confounders complicate analyses of time-varying treatment effects and causal mediation. Conditioning on these variables naively to estimate marginal effects may i…

stat.AP2018

Residual Balancing: A Method of Constructing Weights for Marginal Structural Models

Xiang Zhou, Geoffrey T. Wodtke

When making causal inferences, post-treatment confounders complicate analyses of time-varying treatment effects. Conditioning on these variables naively to estimate marginal effect…