research
∙
08/13/2022
Sensitivity to Unobserved Confounding in Studies with Factor-structured Outcomes
We propose an approach for assessing sensitivity to unobserved confoundi...
share
research
∙
11/15/2021
Bayesian Inference and Partial Identification in Multi-Treatment Causal Inference with Unobserved Confounding
In causal estimation problems, the parameter of interest is often only p...
research
∙
05/14/2021
Learning Gaussian Graphical Models with Latent Confounders
Gaussian Graphical models (GGM) are widely used to estimate the network ...
research
∙
04/12/2021
Deconfounding Scores: Feature Representations for Causal Effect Estimation with Weak Overlap
A key condition for obtaining reliable estimates of the causal effect of...
research
∙
02/18/2021
Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding
Recent work has focused on the potential and pitfalls of causal identifi...
research
∙
10/01/2020
Reducing Subspace Models for Large-Scale Covariance Regression
We develop an envelope model for joint mean and covariance regression in...
research
∙
07/21/2020
Modeling Player and Team Performance in Basketball
In recent years, analytics has started to revolutionize the game of bask...
research
∙
09/02/2018