1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ME2024
Aggregate Bayesian Causal Forests: The ABCs of Flexible Causal Inference for Hierarchically Structured Data
Dan R. C. Thal, Lauren V. Forrow, Erin R. Lipman +2
This paper introduces aggregate Bayesian Causal Forests (aBCF), a new Bayesian model for causal inference using aggregated data. Aggregated data are common in policy evaluations wh…
stat.ME2023
Estimating Causal Impacts of Scaling a Voluntary Policy Intervention
Irina Degtiar, Mariel Finucane
Evaluations often inform future program implementation decisions. However, the implementation context may differ, sometimes substantially, from the evaluation study context. This d…
stat.ME2021★ 1 cited
Absolute and Relative Bias in Eight Common Observational Study Designs: Evidence from a Meta-analysis
Jelena Zurovac, Thomas D. Cook, John Deke +5
Observational studies are needed when experiments are not possible. Within study comparisons (WSC) compare observational and experimental estimates that test the same hypothesis us…