1 citations · 1 across the 5 of their papers we have counts for
5 papers
Causal Effects of Modified Treatment Policies under Positivity Violations: A Partial Identification Approach
Taehyeon Koo, Elizabeth A. Stuart, Kara E. Rudolph +1
Modified treatment policies (MTPs) are interventions based on each individual's natural treatment value. We study mean outcomes under MTPs for continuous treatments, including expo…
Synthetic Control with Weight Uncertainty: Robust Identification and Statistical Inference
Taehyeon Koo, Zijian Guo
The synthetic control method estimates causal effects by comparing a treated unit with weighted controls matched on its pre-treatment trajectory. However, validity can be compromis…
Design-based Causal Inference for Incomplete Block Designs
Taehyeon Koo, Nicole E. Pashley
Researchers often turn to block randomization to increase the precision of their inference or due to practical considerations, such as in multisite trials. However, if the number o…
RobustIV and controlfunctionIV: Causal Inference for Linear and Nonlinear Models with Invalid Instrumental Variables
Taehyeon Koo, Youjin Lee, Dylan S. Small +1
We present R software packages RobustIV and controlfunctionIV for causal inference with possibly invalid instrumental variables. RobustIV focuses on the linear outcome model. It im…
An Invariant Test for Equality of Two Large Scale Covariance Matrices
Taehyeon Koo, Seonghun Cho, Johan Lim
In this work, we are motivated by the recent work of Zhang et al. (2019) and study a new invariant test for equality of two large scale covariance matrices. Two modified likelihood…