53 citations · 172 across the 26 of their papers we have counts for
5 papers · 1 filter
Bayesian Causal Forests & the 2022 ACIC Data Challenge: Scalability and Sensitivity
Ajinkya H. Kokandakar, Hyunseung Kang, Sameer K. Deshpande
We demonstrate how Hahn et al.'s Bayesian Causal Forests model (BCF) can be used to estimate conditional average treatment effects for the longitudinal dataset in the 2022 American…
A Robust, Differentially Private Randomized Experiment for Evaluating Online Educational Programs With Sensitive Student Data
Manjusha Kancharla, Hyunseung Kang
Randomized control trials (RCTs) have been the gold standard to evaluate the effectiveness of a program, policy, or treatment on an outcome of interest. However, many RCTs assume t…
Minimum Resource Threshold Policy Under Partial Interference
Chan Park, Guanhua Chen, Menggang Yu +1
When developing policies for prevention of infectious diseases, policymakers often set specific, outcome-oriented targets to achieve. For example, when developing a vaccine allocat…
ivmodel: An R Package for Inference and Sensitivity Analysis of Instrumental Variables Models with One Endogenous Variable
Hyunseung Kang, Yang Jiang, Qingyuan Zhao +1
We present a comprehensive R software ivmodel for analyzing instrumental variables with one endogenous variable. The package implements a general class of estimators called k- clas…
Full Matching Approach to Instrumental Variables Estimation with Application to the Effect of Malaria on Stunting
Hyunseung Kang, Benno Kreuels, Jürgen May +1
Most previous studies of the causal relationship between malaria and stunting have been studies where potential confounders are controlled via regression-based methods, but these s…