activity
20152023
most citedCausal inference for ordinal outcomes

14 citations · 18 across the 6 of their papers we have counts for

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5 papers · 1 filter

stat.ME2023

Matched Machine Learning: A Generalized Framework for Treatment Effect Inference With Learned Metrics

Marco Morucci, Cynthia Rudin, Alexander Volfovsky

We introduce Matched Machine Learning, a framework that combines the flexibility of machine learning black boxes with the interpretability of matching, a longstanding tool in obser…

stat.ME20213 cited

Density Regression with Bayesian Additive Regression Trees

Vittorio Orlandi, Jared Murray, Antonio Linero +1

Flexibly modeling how an entire density changes with covariates is an important but challenging generalization of mean and quantile regression. While existing methods for density r…

stat.ME20211 cited

Likelihood-based inference for partially observed stochastic epidemics with individual heterogeneity

Fan Bu, Allison E. Aiello, Alexander Volfovsky +1

We develop a stochastic epidemic model progressing over dynamic networks, where infection rates are heterogeneous and may vary with individual-level covariates. The joint dynamics…

stat.ME2021

Latent Community Adaptive Network Regression

Heather Mathews, Alexander Volfovsky

The study of network data in the social and health sciences frequently concentrates on two distinct tasks (1) detecting community structures among nodes and (2) associating covaria…

stat.ME201514 cited

Causal inference for ordinal outcomes

Alexander Volfovsky, Edoardo M. Airoldi, Donald B. Rubin

Many outcomes of interest in the social and health sciences, as well as in modern applications in computational social science and experimentation on social media platforms, are or…