activity
20182020
most citedEstimating heterogeneous effects of continuous exposures using Bayesian tree ensembles: revisiting the impact of abortion rates on crime

10 citations · 10 across the 1 of their papers we have counts for

collaborators

5 papers

stat.AP202010 cited

Estimating heterogeneous effects of continuous exposures using Bayesian tree ensembles: revisiting the impact of abortion rates on crime

Spencer Woody, Carlos M. Carvalho, P. Richard Hahn +1

In estimating the causal effect of a continuous exposure or treatment, it is important to control for all confounding factors. However, most existing methods require parametric spe…

stat.ME2019

Bayesian Model Calibration for Extrapolative Prediction via Gibbs Posteriors

Spencer Woody, Novin Ghaffari, Lauren Hund

The current standard Bayesian approach to model calibration, which assigns a Gaussian process prior to the discrepancy term, often suffers from issues of unidentifiability and comp…

stat.ME2019

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…

stat.ME2019

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…

stat.ME2018

Optimal post-selection inference for sparse signals: a nonparametric empirical-Bayes approach

Spencer Woody, Oscar Hernan Madrid Padilla, James G. Scott

Many recently developed Bayesian methods have focused on sparse signal detection. However, much less work has been done addressing the natural follow-up question: how to make valid…