17 citations · 36 across the 11 of their papers we have counts for
6 papers · 1 filter
Differential recall bias in estimating treatment effects in observational studies
Suhwan Bong, Kwonsang Lee, Francesca Dominici
Observational studies are frequently used to estimate the effect of an exposure or treatment on an outcome. To obtain an unbiased estimate of the treatment effect, it is crucial to…
Accounting for recall bias in case-control studies: a causal inference approach
Kwonsang Lee, Francesca Dominici
A case-control study is designed to help determine if an exposure is associated with an outcome. However, since case-control studies are retrospective, they are often subject to re…
Causal Rule Ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects
Falco J. Bargagli-Stoffi, Riccardo Cadei, Kwonsang Lee +1
In health and social sciences, it is critically important to identify subgroups of the study population where there is notable heterogeneity of treatment effects (HTE) with respect…
Sensitivity analyses for average treatment effects when outcome is censored by death in instrumental variable models
Kwonsang Lee, Scott A. Lorch, Dylan S. Small
Two problems that arise in making causal inferences for non-mortality outcomes such as bronchopulmonary dysplasia (BPD) are unmeasured confounding and censoring by death, i.e., the…
A powerful approach to the study of moderate effect modification in observational studies
Kwonsang Lee, Dylan S. Small, Paul R. Rosenbaum
Effect modification means the magnitude or stability of a treatment effect varies as a function of an observed covariate. Generally, larger and more stable treatment effects are in…
A Nonparametric Likelihood Approach for Inference in Instrumental Variable Models
Kwonsang Lee, Bhaswar B. Bhattacharya, Jing Qin +1
Instrumental variable methods allow for inference about the treatment effect by controlling for unmeasured confounding in randomized experiments with noncompliance. However, many s…