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20182025
most citedModel interpretation through lower-dimensional posterior summarization

38 citations · 61 across the 7 of their papers we have counts for

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5 papers · 1 filter

stat.ME2020★ 2 cited

Bayesian inference for treatment effects under nested subsets of controls

Spencer Woody, Carlos M. Carvalho, Jared S. Murray

When constructing a model to estimate the causal effect of a treatment, it is necessary to control for other factors which may have confounding effects. Because the ignorability as…

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★ 38 cited

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★ 11 cited

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…