Source Themes

A framework for causal inference with bipartite interference from observational, time series data with a random bipartite network.

Statistical software manuscript introducing the geocausal R package for spatio-temporal causal inference.

We propose a latent factor interaction model for networks measured with error, and a variable importance metric for latent models. We use the model to address the geographic and taxonomic bias of ecological studies of species' interactions, and identify the important bird and plant covariates for forming and detecting interactions.

Estimating the causal effect of the Hospital Readmissions Reduction on program on patient readmission and mortality rates.

Evaluating the effect of a point pattern treatment on a point pattern outcome measured over time.

We introduce a framework for estimating causal effects of binary and continuous treatments in high dimensions. We show how posterior distributions of treatment and outcome models can be used together with doubly robust estimators. We propose an …

Estimation of tensor regression coefficients on a soft version of the PARAFAC approximation.

Causal inference for subgroup analysis and the Connect-S plot.