1 citations · 1 across the 2 of their papers we have counts for
4 papers
Sensitivity Analysis for the Average Treatment Effect under Discrete Unobserved Confounders
Sung Jae Jun, Federico Zincenko
We model unobserved confounding through an unknown finite number of latent types. This assumption induces finite-mixture representations of the treated and control outcome distribu…
Average Adjusted Association: Efficient Estimation with High Dimensional Confounders
Sung Jae Jun, Sokbae Lee
The log odds ratio is a well-established metric for evaluating the association between binary outcome and exposure variables. Despite its widespread use, there has been limited dis…
Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions
Sung Jae Jun, Sokbae Lee
We study causal inference under case-control and case-population sampling. Specifically, we focus on the binary-outcome and binary-treatment case, where the parameters of interest…
Identifying the Effect of Persuasion
Sung Jae Jun, Sokbae Lee
This paper examines a commonly used measure of persuasion whose precise interpretation has been obscure in the literature. By using the potential outcome framework, we define the c…