8 citations · 17 across the 13 of their papers we have counts for
13 papers
Causal Inference on Sequential Treatments via Tensor Completion
Chenyin Gao, Han Chen, Anru R. Zhang +1
Marginal Structural Models (MSMs) are popular for causal inference of sequential treatments in longitudinal observational studies, which however are sensitive to model misspecifica…
Doubly robust omnibus sensitivity analysis of externally controlled trials with intercurrent events
Chenyin Gao, Xiang Zhang, Shu Yang
Externally controlled trials are crucial in clinical development when randomized controlled trials are unethical or impractical. These trials consist of a full treatment arm with t…
Doubly protected estimation for survival outcomes utilizing external controls for randomized clinical trials
Chenyin Gao, Shu Yang, Mingyang Shan +3
Censored survival data are common in clinical trials, but small control groups can pose challenges, particularly in rare diseases or where balanced randomization is impractical. Re…
Causal Customer Churn Analysis with Low-rank Tensor Block Hazard Model
Chenyin Gao, Zhiming Zhang, Shu Yang
This study introduces an innovative method for analyzing the impact of various interventions on customer churn, using the potential outcomes framework. We present a new causal mode…
Real Effect or Bias? Best Practices for Evaluating the Robustness of Real-World Evidence through Quantitative Sensitivity Analysis for Unmeasured Confounding
Douglas Faries, Chenyin Gao, Xiang Zhang +7
The assumption of no unmeasured confounders is a critical but unverifiable assumption required for causal inference yet quantitative sensitivity analyses to assess robustness of re…
Improving randomized controlled trial analysis via data-adaptive borrowing
Chenyin Gao, Shu Yang, Mingyang Shan +3
In recent years, real-world external controls have grown in popularity as a tool to empower randomized placebo-controlled trials, particularly in rare diseases or cases where balan…
Pretest estimation in combining probability and non-probability samples
Chenyin Gao, Shu Yang
Multiple heterogeneous data sources are becoming increasingly available for statistical analyses in the era of big data. As an important example in finite-population inference, we…
Transporting survival of an HIV clinical trial to the external target populations
Dasom Lee, Sujit Ghosh, Shu Yang
Due to the heterogeneity of the randomized controlled trial (RCT) and external target populations, the estimated treatment effect from the RCT is not directly applicable to the tar…
Enhancing convolutional neural network generalizability via low-rank weight approximation
Chenyin Gao, Shu Yang, Anru R. Zhang
Noise is ubiquitous during image acquisition. Sufficient denoising is often an important first step for image processing. In recent decades, deep neural networks (DNNs) have been w…
Soft calibration for selection bias problems under mixed-effects models
Chenyin Gao, Shu Yang, Jae Kwang Kim
Calibration weighting has been widely used to correct selection biases in non-probability sampling, missing data, and causal inference. The main idea is to calibrate the biased sam…
Nearest neighbor ratio imputation with incomplete multi-nomial outcome in survey sampling
Chenyin Gao, Katherine Jenny Thompson, Shu Yang +1
Nonresponse is a common problem in survey sampling. Appropriate treatment can be challenging, especially when dealing with detailed breakdowns of totals. Often, the nearest neighbo…
Estimating spatially varying health effects of wildland fire smoke using mobile health data
Lili Wu, Chenyin Gao, Shu Yang +2
Wildland fire smoke exposures are an increasing threat to public health, and thus there is a growing need for studying the effects of protective behaviors on reducing health outcom…
Elastic Integrative Analysis of Randomized Trial and Real-World Data for Treatment Heterogeneity Estimation
Shu Yang, Chenyin Gao, Donglin Zeng +1
We propose a test-based elastic integrative analysis of the randomized trial and real-world data to estimate treatment effect heterogeneity with a vector of known effect modifiers.…