157 citations · 163 across the 6 of their papers we have counts for
6 papers
What does not get observed can be used to make age curves stronger: estimating player age curves using regression and imputation
Michael Schuckers, Michael Lopez, Brian Macdonald
The impact of player age on performance has received attention across sport. Most research has focused on the performance of players at each age, ignoring the reality that age like…
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…
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…
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…
Estimation of causal effects with multiple treatments: a review and new ideas
Michael J Lopez, Roee Gutman
The propensity score is a common tool for estimating the causal effect of a binary treatment in observational data. In this setting, matching, subclassification, imputation, or inv…
Estimating the average treatment effects of nutritional label use using subclassification with regression adjustment
Michael Lopez, Roee Gutman
Propensity score methods are common for estimating a binary treatment effect when treatment assignment is not randomized. When exposure is measured on an ordinal scale (i.e., low -…