8 citations · 13 across the 4 of their papers we have counts for
5 papers · 1 filter
On the Distinction Between "Conditional Average Treatment Effects" (CATE) and "Individual Treatment Effects" (ITE) Under Ignorability Assumptions
Brian G. Vegetabile
Recent years have seen a swell in methods that focus on estimating "individual treatment effects". These methods are often focused on the estimation of heterogeneous treatment effe…
Balancing Higher Moments Matters for Causal Estimation: Further Context for the Results of Setodji et al. (2017)
Melody Y. Huang, Brian G. Vegetabile, Lane F. Burgette +2
We expand upon the simulation study of Setodji et al. (2017) which compared three promising balancing methods when assessing the average treatment effect on the treated for binary…
Reducing bias in difference-in-differences models using entropy balancing
Matthew Cefalu, Brian G. Vegetabile, Michael Dworsky +2
This paper illustrates the use of entropy balancing in difference-in-differences analyses when pre-intervention outcome trends suggest a possible violation of the parallel trends a…
Nonparametric Estimation of Population Average Dose-Response Curves using Entropy Balancing Weights for Continuous Exposures
Brian G. Vegetabile, Beth Ann Griffin, Donna L. Coffman +2
Weighted estimators are commonly used for estimating exposure effects in observational settings to establish causal relations. These estimators have a long history of development w…
Estimating the Entropy Rate of Finite Markov Chains with Application to Behavior Studies
Brian Vegetabile, Jenny Molet, Tallie Z. Baram +1
Predictability of behavior has emerged an an important characteristic in many fields including biology, medicine, and marketing. Behavior can be recorded as a sequence of actions p…