53 citations · 172 across the 26 of their papers we have counts for
6 papers · 1 filter
Inference After Selecting Plausibly Valid Instruments with Application to Mendelian Randomization
Nan Bi, Hyunseung Kang, Jonathan Taylor
Mendelian randomization (MR) is a popular method in genetic epidemiology to estimate the effect of an exposure on an outcome by using genetic instruments. These instruments are oft…
Debiased Inverse-Variance Weighted Estimator in Two-Sample Summary-Data Mendelian Randomization
Ting Ye, Jun Shao, Hyunseung Kang
Mendelian randomization (MR) has become a popular approach to study the effect of a modifiable exposure on an outcome by using genetic variants as instrumental variables. A challen…
Weak-Instrument Robust Tests in Two-Sample Summary-Data Mendelian Randomization
Sheng Wang, Hyunseung Kang
Mendelian randomization (MR) has been a popular method in genetic epidemiology to estimate the effect of an exposure on an outcome using genetic variants as instrumental variables…
A Groupwise Approach for Inferring Heterogeneous Treatment Effects in Causal Inference
Chan Park, Hyunseung Kang
Recently, there has been great interest in estimating the conditional average treatment effect using flexible machine learning methods. However, in practice, investigators often ha…
Detecting Heterogeneous Treatment Effect with Instrumental Variables
Michael Johnson, Jiongyi Cao, Hyunseung Kang
There is an increasing interest in estimating heterogeneity in causal effects in randomized and observational studies. However, little research has been conducted to understand het…
Increasing Power for Observational Studies of Aberrant Response: An Adaptive Approach
Siyu Heng, Hyunseung Kang, Dylan S. Small +1
In many observational studies, the interest is in the effect of treatment on bad, aberrant outcomes rather than the average outcome. For such settings, the traditional approach is…