4 citations · 9 across the 7 of their papers we have counts for
7 papers
Multiply robust estimation for causal survival analysis with treatment noncompliance
Chao Cheng, Bo Liu, Lisa Wruck +1
Comparative effectiveness research frequently addresses a time-to-event outcome and can require unique considerations in the presence of treatment noncompliance. Motivated by the c…
Correcting for bias due to mismeasured exposure in mediation analysis with a survival outcome
Chao Cheng, Donna Spiegelman, Fan Li
Mediation analysis is widely used in health science research to evaluate the extent to which an intermediate variable explains an observed exposure-outcome relationship. However, t…
Doubly robust estimation and sensitivity analysis for marginal structural quantile models
Chao Cheng, Liangyuan Hu, Fan Li
The marginal structure quantile model (MSQM) provides a unique lens to understand the causal effect of a time-varying treatment on the full distribution of potential outcomes. Unde…
A repeated measures approach to pooled and calibrated biomarker data
Abigail Sloan, Chao Cheng, Bernard Rosner +3
Participant level meta-analysis across multiple studies increases the sample size for pooled analyses, thereby improving precision in effect estimates and enabling subgroup analyse…
Estimating the natural indirect effect and the mediation proportion via the product method
Chao Cheng, Donna Spiegelman, Fan Li
The natural indirect effect (NIE) and mediation proportion (MP) are two measures of primary interest in mediation analysis. The standard approach for estimating NIE and MP is throu…
Addressing Extreme Propensity Scores in Estimating Counterfactual Survival Functions via the Overlap Weights
Chao Cheng, Fan Li, Laine Thomas
The inverse probability weighting approach is popular for evaluating treatment effects in observational studies, but extreme propensity scores could bias the estimator and induce e…
Parallel subgroup analysis of high-dimensional data via M-regression
Chao Cheng, Xingdong Feng
It becomes an interesting problem to identify subgroup structures in data analysis as populations are probably heterogeneous in practice. In this paper, we consider M-estimators to…