13 citations · 23 across the 15 of their papers we have counts for
15 papers
On Defense of the Hazard Ratio
Andrew Ying, Ronghui Xu
In this short communication, we describe the recent debate on whether the hazard function should be used for causal inference in time-to-event studies and consider three different…
Doubly Robust Estimation under Covariate-Induced Dependent Left Truncation
Yuyao Wang, Andrew Ying, Ronghui Xu
In prevalent cohort studies with follow-up, the time-to-event outcome is subject to left truncation leading to selection bias. For estimation of the distribution of time-to-event,…
Doubly Robust Inference for Hazard Ratio under Informative Censoring with Machine Learning
Jiyu Luo, Ronghui Xu
Randomized clinical trials with time-to-event outcomes have traditionally used the log-rank test followed by the Cox proportional hazards (PH) model to estimate the hazard ratio be…
Marginal Structural Illness-Death Models for Semi-Competing Risks Data
Yiran Zhang, Andrew Ying, Steve Edland +2
The three state illness death model has been established as a general approach for regression analysis of semi competing risks data. For observational data the marginal structural…
Doubly Robust Estimation of the Hazard Difference for Competing Risks Data
Denise Rava, Ronghui Xu
We consider the conditional treatment effect for competing risks data in observational studies. While it is described as a constant difference between the hazard functions given th…
Causal Effects of Prenatal Drug Exposure on Birth Defects with Missing by Terathanasia
Andrew Ying, Ronghui Xu, Christina D. Chambers +1
A recent cohort study revealed a positive correlate between major structural birth defects in infants and a certain medication taken by pregnant women. To draw valid causal inferen…
Explained Variation under the Additive Hazards Model
Denise Rava, Ronghui Xu
We study explained variation under the additive hazards regression model for right-censored data. We consider different approaches for developing such a measure, and focus on one t…
Sensitivity Analysis of Treatment Effect to Unmeasured Confounding in Observational Studies with Survival and Competing Risks Outcomes
Rong Huang, Ronghui Xu, Parambir S. Dulai
No unmeasured confounding is often assumed in estimating treatment effects in observational data when using approaches such as propensity scores and inverse probability weighting.…
Estimating Treatment Effect under Additive Hazards Models with High-dimensional Covariates
Jue Hou, Jelena Bradic, Ronghui Xu
Estimating causal effects for survival outcomes in the high-dimensional setting is an extremely important topic for many biomedical applications as well as areas of social sciences…
Two-Stage Residual Inclusion under the Additive Hazards Model - An Instrumental Variable Approach with Application to SEER-Medicare Linked Data
Andrew Ying, Ronghui Xu, James Murphy
Instrumental variable is an essential tool for addressing unmeasured confounding in observational studies. Two stage predictor substitution (2SPS) estimator and two stage residual…
Semiparametric Sieve Maximum Likelihood Estimation Under Cure Model with Partly Interval Censored and Left Truncated Data for Application to Spontaneous Abortion Data
Yuan Wu, Christina D. Chambers, Ronghui Xu
This work was motivated by observational studies in pregnancy with spontaneous abortion (SAB) as outcome. Clearly some women experience the SAB event but the rest do not. In additi…
Fine-Gray competing risks model with high-dimensional covariates: estimation and Inference
Jue Hou, Jelena Bradic, Ronghui Xu
The purpose of this paper is to construct confidence intervals for the regression coefficients in the Fine-Gray model for competing risks data with random censoring, where the numb…
High-Dimensional Variable Selection and Prediction under Competing Risks with Application to SEER-Medicare Linked Data
Jiayi Hou, Anthony Paravati, Ronghui Xu +1
Competing risk analysis considers event times due to multiple causes, or of more than one event types. Commonly used regression models for such data include 1) cause-specific hazar…
The Impact of Confounder Selection in Propensity Scores for Rare Events Data - with Applications to Birth Defects
Ronghui Xu, Jue Hou, Christina D. Chambers
Our work was motivated by a recent study on birth defects of infants born to pregnant women exposed to a certain medication for treating chronic diseases. Outcomes such as birth de…
A Nonparametric Maximum Likelihood Approach for Partially Observed Cured Data with Left Truncation and Right-Censoring
Jue Hou, Christina D. Chambers, Ronghui Xu
Partially observed cured data occur in the analysis of spontaneous abortion (SAB) in observational studies in pregnancy. In contrast to the traditional cured data, such data has an…