79 citations · 162 across the 13 of their papers we have counts for
16 papers
Decoupling Shrinkage and Selection in Gaussian Linear Factor Analysis
Henrique Bolfarine, Carlos M. Carvalho, Hedibert F. Lopes +1
Factor Analysis is a popular method for modeling dependence in multivariate data. However, determining the number of factors and obtaining a sparse orientation of the loadings are…
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…
A projection approach for multiple monotone regression
Lizhen Lin, Brian St. Thomas, Walter W. Piegorsch +2
Shape-constrained inference has wide applicability in bioassay, medicine, economics, risk assessment, and many other fields. Although there has been a large amount of work on monot…
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…
Targeted Smooth Bayesian Causal Forests: An analysis of heterogeneous treatment effects for simultaneous versus interval medical abortion regimens over gestation
Jennifer E. Starling, Jared S. Murray, Patricia A. Lohr +3
We introduce Targeted Smooth Bayesian Causal Forests (tsBCF), a nonparametric Bayesian approach for estimating heterogeneous treatment effects which vary smoothly over a single cov…
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…