1 citations · 1 across the 5 of their papers we have counts for
5 papers
Amortized Inference for Correlated Discrete Choice Models via Equivariant Neural Networks
Easton Huch, Michael Keane
Discrete choice models are fundamental tools in management science, economics, and marketing for understanding and predicting decision-making. Logit-based models are dominant in ap…
Robust Bayesian Inference of Causal Effects via Randomization Distributions
Easton Huch, Fred Feinberg, Walter Dempsey
We present a general framework for Bayesian inference of causal effects that delivers provably robust inferences founded on design-based randomization of treatments. The framework…
Stable Central Limit Theorems for Discrete-Time Lag Martingale Difference Arrays: Applications to Dynamic Causal Inference
Walter Dempsey, Easton Huch
Recent work in dynamic causal inference introduced a class of discrete-time stochastic processes that generalize martingale difference sequences and arrays as follows: the random v…
Data integration methods for micro-randomized trials
Easton Huch, Inbal Nahum-Shani, Lindsey Potter +3
Existing statistical methods for the analysis of micro-randomized trials (MRTs) are designed to estimate causal excursion effects using data from a single MRT. In practice, however…
RoME: A Robust Mixed-Effects Bandit Algorithm for Optimizing Mobile Health Interventions
Easton K. Huch, Jieru Shi, Madeline R. Abbott +3
Mobile health leverages personalized and contextually tailored interventions optimized through bandit and reinforcement learning algorithms. In practice, however, challenges such a…