activity
20182020
most citedTwo Robust Tools for Inference about Causal Effects with Invalid Instruments

2 citations · 2 across the 2 of their papers we have counts for

collaborators

5 papers

stat.ME2020

Doubly Robust Nonparametric Instrumental Variable Estimators for Survival Outcomes

Youjin Lee, Edward H. Kennedy, Nandita Mitra

Instrumental variable (IV) methods allow us the opportunity to address unmeasured confounding in causal inference. However, most IV methods are only applicable to discrete or conti…

stat.ME20202 cited

Two Robust Tools for Inference about Causal Effects with Invalid Instruments

Hyunseung Kang, Youjin Lee, T. Tony Cai +1

Instrumental variables have been widely used to estimate the causal effect of a treatment on an outcome. Existing confidence intervals for causal effects based on instrumental vari…

stat.AP2019

Partially Pooled Propensity Score Models for Average Treatment Effect Estimation with Multilevel Data

Youjin Lee, Trang Q. Nguyen, Elizabeth A. Stuart

Causal inference analyses often use existing observational data, which in many cases has some clustering of individuals. In this paper we discuss propensity score weighting methods…

stat.AP2019

Network Dependence Can Lead to Spurious Associations and Invalid Inference

Youjin Lee, Elizabeth L. Ogburn

Researchers across the health and social sciences generally assume that observations are independent, even while relying on convenience samples that draw subjects from one or a sma…

stat.ME2018

Causal inference, social networks, and chain graphs

Elizabeth L. Ogburn, Ilya Shpitser, Youjin Lee

Traditionally, statistical and causal inference on human subjects rely on the assumption that individuals are independently affected by treatments or exposures. However, recently t…