activity
20172021
most citedEnabling Counterfactual Survival Analysis with Balanced Representations

21 citations · 56 across the 11 of their papers we have counts for

collaborators

11 papers

cs.LG2021

Hölder Bounds for Sensitivity Analysis in Causal Reasoning

Serge Assaad, Shuxi Zeng, Henry Pfister +2

We examine interval estimation of the effect of a treatment T on an outcome Y given the existence of an unobserved confounder U. Using Hölder's inequality, we derive a set of bound…

stat.ME2021

A Causal Mediation Model for Longitudinal Mediators and Survival Outcomes with an Application to Animal Behavior

Shuxi Zeng, Elizabeth C. Lange, Elizabeth A. Archie +3

In animal behavior studies, a common goal is to investigate the causal pathways between an exposure and outcome, and a mediator that lies in between. Causal mediation analysis prov…

stat.ME2021★ 1 cited

Propensity Score Weighting Analysis of Survival Outcomes Using Pseudo-observations

Shuxi Zeng, Fan Li, Liangyuan Hu

Survival outcomes are common in comparative effectiveness studies and require unique handling because they are usually incompletely observed due to right-censoring. A ``once for al…

stat.ML2020★ 2 cited

Double Robust Representation Learning for Counterfactual Prediction

Shuxi Zeng, Serge Assaad, Chenyang Tao +3

Causal inference, or counterfactual prediction, is central to decision making in healthcare, policy and social sciences. To de-bias causal estimators with high-dimensional data in…

stat.ML2020★ 4 cited

Counterfactual Representation Learning with Balancing Weights

Serge Assaad, Shuxi Zeng, Chenyang Tao +5

A key to causal inference with observational data is achieving balance in predictive features associated with each treatment type. Recent literature has explored representation lea…

cs.LG2020

Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction

Shuxi Zeng, Murat Ali Bayir, Joesph J. Pfeiffer +2

It is often critical for prediction models to be robust to distributional shifts between training and testing data. From a causal perspective, the challenge is to distinguish the s…

stat.AP2020★ 10 cited

Causal Mediation Analysis for Sparse and Irregular Longitudinal Data

Shuxi Zeng, Stacy Rosenbaum, Elizabeth Archie +2

Causal mediation analysis seeks to investigate how the treatment effect of an exposure on outcomes is mediated through intermediate variables. Although many applications involve lo…

stat.AP2020★ 4 cited

Is being an only child harmful to psychological health?: Evidence from an instrumental variable analysis of China's One-Child Policy

Shuxi Zeng, Fan Li, Peng Ding

This paper evaluates the effects of being an only child in a family on psychological health, leveraging data on the One-Child Policy in China. We use an instrumental variable appro…

stat.ML2020★ 21 cited

Enabling Counterfactual Survival Analysis with Balanced Representations

Paidamoyo Chapfuwa, Serge Assaad, Shuxi Zeng +3

Balanced representation learning methods have been applied successfully to counterfactual inference from observational data. However, approaches that account for survival outcomes…

stat.ME2020★ 5 cited

Propensity Score Weighting for Covariate Adjustment in Randomized Clinical Trials

Shuxi Zeng, Fan Li, Rui Wang

Chance imbalance in baseline characteristics is common in randomized clinical trials. Regression adjustment such as the analysis of covariance (ANCOVA) is often used to account for…

stat.ML2017★ 9 cited

RNN-based counterfactual prediction, with an application to homestead policy and public schooling

Jason Poulos, Shuxi Zeng

This paper proposes a method for estimating the effect of a policy intervention on an outcome over time. We train recurrent neural networks (RNNs) on the history of control unit ou…