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07/04/2023
A Double Machine Learning Approach to Combining Experimental and Observational Data
Experimental and observational studies often lack validity due to untest...
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05/12/2023
Identifying World Events in Dynamic International Relations Data Using a Latent Space Model
Dynamic network data have become ubiquitous in social network analysis, ...
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04/03/2023
Matched Machine Learning: A Generalized Framework for Treatment Effect Inference With Learned Metrics
We introduce Matched Machine Learning, a framework that combines the fle...
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02/23/2023
From Feature Importance to Distance Metric: An Almost Exact Matching Approach for Causal Inference
Our goal is to produce methods for observational causal inference that a...
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12/07/2022
Neighborhood Adaptive Estimators for Causal Inference under Network Interference
Estimating causal effects has become an integral part of most applied fi...
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06/16/2022
Bias and Excess Variance in Election Polling: A Not-So-Hidden Markov Model
With historic misses in the 2016 and 2020 US Presidential elections, int...
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03/09/2022
Why Interpretable Causal Inference is Important for High-Stakes Decision Making for Critically Ill Patients and How To Do It
Many fundamental problems affecting the care of critically ill patients ...
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12/22/2021
Density Regression with Bayesian Additive Regression Trees
Flexibly modeling how an entire density changes with covariates is an im...
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12/15/2021
Likelihood-based inference for partially observed stochastic epidemics with individual heterogeneity
We develop a stochastic epidemic model progressing over dynamic networks...
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12/11/2021
Latent Community Adaptive Network Regression
The study of network data in the social and health sciences frequently c...
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06/15/2021
Author Clustering and Topic Estimation for Short Texts
Analysis of short text, such as social media posts, is extremely difficu...
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01/06/2021
dame-flame: A Python Library Providing Fast Interpretable Matching for Causal Inference
dame-flame is a Python package for performing matching for observational...
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03/03/2020
Adaptive Hyper-box Matching for Interpretable Individualized Treatment Effect Estimation
We propose a matching method for observational data that matches units w...
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03/02/2020
Almost-Matching-Exactly for Treatment Effect Estimation under Network Interference
We propose a matching method that recovers direct treatment effects from...
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11/05/2019
Gaussian Mixture Models for Stochastic Block Models with Non-Vanishing Noise
Community detection tasks have received a lot of attention across statis...
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10/09/2019
Likelihood-based Inference for Partially Observed Epidemics on Dynamic Networks
We propose a generative model and an inference scheme for epidemic proce...
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07/04/2019
The Geometry of Community Detection via the MMSE Matrix
The information-theoretic limits of community detection have been studie...
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06/27/2019
Interpretable Almost-Matching-Exactly With Instrumental Variables
Uncertainty in the estimation of the causal effect in observational stud...
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11/18/2018
MALTS: Matching After Learning to Stretch
We introduce a flexible framework for matching in causal inference that ...
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06/18/2018
Collapsing-Fast-Large-Almost-Matching-Exactly: A Matching Method for Causal Inference
We aim to create the highest possible quality of treatment-control match...
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06/18/2018
SMOGS: Social Network Metrics of Game Success
This paper develops metrics from a social network perspective that are d...
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01/22/2018
Propensity score methodology in the presence of network entanglement between treatments
In experimental design and causal inference, it may happen that the trea...
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07/19/2017
FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference
A classical problem in causal inference is that of matching, where treat...
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06/25/2015