3 papers
stat.ME2022
Graph-Based Tests for Multivariate Covariate Balance Under Multi-Valued Treatments
Eric A. Dunipace
We propose the use of non-parametric, graph-based tests to assess the distributional balance of covariates in observational studies with multi-valued treatments. Our tests utilize…
stat.ME2021
Optimal transport weights for causal inference
Eric Dunipace
Imbalance in covariate distributions leads to biased estimates of causal effects. Weighting methods attempt to correct this imbalance but rely on specifying models for the treatmen…
stat.ME2020
Interpretable Model Summaries Using the Wasserstein Distance
Eric Dunipace, Lorenzo Trippa
Statistical models often include thousands of parameters. However, large models decrease the investigator's ability to interpret and communicate the estimated parameters. Reducing…