42 citations · 55 across the 15 of their papers we have counts for
18 papers
A spatial interference approach to account for mobility in air pollution studies with multivariate continuous treatments
Heejun Shin, Danielle Braun, Kezia Irene +2
We develop new methodology to improve our understanding of the causal effects of multivariate air pollution exposures on public health accounting for mobility. Typically, in enviro…
All models are wrong, but which are useful? Comparing parametric and nonparametric estimation of causal effects in finite samples
Kara E. Rudolph, Nicholas Williams, Caleb H. Miles +2
There is a long-standing debate in the statistical, epidemiological and econometric fields as to whether nonparametric estimation that uses data-adaptive methods, like machine lear…
The How and Why of Bayesian Nonparametric Causal Inference
Antonio R. Linero, Joseph L. Antonelli
Spurred on by recent successes in causal inference competitions, Bayesian nonparametric (and high-dimensional) methods have recently seen increased attention in the causal inferenc…
Improved inference for doubly robust estimators of heterogeneous treatment effects
Heejun Shin, Joseph Antonelli
We propose a doubly robust approach to characterizing treatment effect heterogeneity in observational studies. We develop a frequentist inferential procedure that utilizes posterio…
Multiple exposure distributed lag models with variable selection
Joseph Antonelli, Ander Wilson, Brent Coull
Distributed lag models are useful in environmental epidemiology as they allow the user to investigate critical windows of exposure, defined as the time period during which exposure…
Robust inference for geographic regression discontinuity designs: assessing the impact of police precincts
Emmett B. Kendall, Brenden Beck, Joseph Antonelli
We study variation in policing outcomes attributable to differential policing practices in New York City (NYC) using geographic regression discontinuity designs (GeoRDDs). By focus…