4 citations · 4 across the 1 of their papers we have counts for
3 papers
stat.ME2020
A flexible sensitivity analysis approach for unmeasured confounding with multiple treatments and a binary outcome with application to SEER-Medicare lung cancer data
Liangyuan Hu, Jungang Zou, Chenyang Gu +3
In the absence of a randomized experiment, a key assumption for drawing causal inference about treatment effects is the ignorable treatment assignment. Violations of the ignorabili…
stat.ME2020★ 4 cited
Estimation of Causal Effects of Multiple Treatments in Observational Studies with a Binary Outcome
Liangyuan Hu, Chenyang Gu, Michael Lopez +2
There is a dearth of robust methods to estimate the causal effects of multiple treatments when the outcome is binary. This paper uses two unique sets of simulations to propose and…
stat.ME2019
The Estimation of Causal Effects of Multiple Treatments in Observational Studies Using Bayesian Additive Regression Trees
Chenyang Gu, Michael J. Lopez, Liangyuan Hu
There is currently a dearth of appropriate methods to estimate the causal effects of multiple treatments when the outcome is binary. For such settings, we propose the use of nonpar…