313 citations · 357 across the 7 of their papers we have counts for
11 papers · 1 filter
Discussion on "Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects" by Hahn, Murray and Carvalho
Liangyuan Hu
Hahn et al. (2020) offers an extensive study to explicate and evaluate the performance of the BCF model in different settings and provides a detailed discussion about its utility i…
Invited Discussion of "A Unified Framework for De-Duplication and Population Size Estimation"
Jared S. Murray
Invited Discussion of "A Unified Framework for De-Duplication and Population Size Estimation", published in Bayesian Analysis. My discussion focuses on two main themes: Providing a…
Assessing Treatment Effect Variation in Observational Studies: Results from a Data Challenge
Carlos Carvalho, Avi Feller, Jared Murray +2
A growing number of methods aim to assess the challenging question of treatment effect variation in observational studies. This special section of "Observational Studies" reports t…
Atlantic Causal Inference Conference (ACIC) Data Analysis Challenge 2017
P. Richard Hahn, Vincent Dorie, Jared S. Murray
This brief note documents the data generating processes used in the 2017 Data Analysis Challenge associated with the Atlantic Causal Inference Conference (ACIC). The focus of the c…
Model interpretation through lower-dimensional posterior summarization
Spencer Woody, Carlos M. Carvalho, Jared S. Murray
Nonparametric regression models have recently surged in their power and popularity, accompanying the trend of increasing dataset size and complexity. While these models have proven…
Scaling Bayesian Probabilistic Record Linkage with Post-Hoc Blocking: An Application to the California Great Registers
Brendan S. McVeigh, Bradley T. Spahn, Jared S. Murray
Probabilistic record linkage (PRL) is the process of determining which records in two databases correspond to the same underlying entity in the absence of a unique identifier. Baye…