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## Joseph Antonelli

Assistant Professor of Statistics

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## Future Blog Post

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## Blog Post number 4

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## Blog Post number 1

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## Mitigating bias in generalized linear mixed models: The case for Bayesian nonparametrics.

Joseph Antonelli, Lorenzo Trippa, and Sebastien Haneuse. Statistical Science, 2016.

## The positive effects of population-based preferential sampling in environmental epidemiology.

Joseph Antonelli, Matthew Cefalu, and Luke Bornn. Biostatistics, 2016.

## Guided Bayesian imputation to adjust for confounding when combining heterogeneous data sources in comparative effectiveness research.

Joseph Antonelli, Corwin Zigler, and Francesca Dominici. Biostatistics, 2017.

## Spatial multiresolution analysis of the effect of PM2.5 on birth weights

Joseph Antonelli, Joel Schwartz, Itai Kloog, and Brent Coull. Annals of Applied Statistics, 2017.

## A synthetic estimator for the efficacy of clinical trials with all or nothing compliance

Joseph Antonelli, Bing Han, and Matthew Cefalu. Statistics in Medicine, 2017.

## Estimating the causal effect of low levels of fine particulate matter on hospitalization.

Maggie Makar*, Joseph Antonelli*, Qian Di, David Cutler, Joel Schwartz, and Francesca Dominici. Epidemiology, 2017.

## Doubly robust matching estimators for high dimensional confounding adjustment.

Joseph Antonelli, Matthew Cefalu, Nathan Palmer, and Denis Agniel. Biometrics, 2018.

## High-dimensional confounding adjustment using continuous spike and slab priors

Joseph Antonelli, Giovanni Parmigiani, and Francesca Dominici. Bayesian Analysis, 2018.

## Averaging causal estimators in high dimensions

Joseph Antonelli and Matthew Cefalu. Journal of Causal Inference, 2020.

## Estimating the health effects of environmental mixtures using Bayesian semiparametric regression and sparsity inducing priors models

Joseph Antonelli, Maitreyi Mazumdar, David Bellinger, David Christiani, Robert Wright, and Brent Coull. The Annals of Applied Statistics, 2020.

## Spike-and-slab group lassos for grouped regression and sparse generalized additive models

Ray Bai*, Gemma Moran*, Joseph Antonelli*, Yong Chen, and Mary Boland. Journal of the American Statistical Association, 2020.

## Causal Inference in high dimensions: A marriage between Bayesian modeling and good frequentist properties

Joseph Antonelli, Georgia Papadogeorgou, and Francesca Dominici. Biometrics, 2020.

## Heterogeneous causal effects of neighborhood policing in New York City with staggered adoption of the policy

Joseph Antonelli and Brenden Beck. ArXiv, 2020.

## Robust inference for geographic regression discontinuity designs: assessing the impact of police precincts

Emmett Kendall, Brenden Beck, and Joseph Antonelli. ArXiv, 2021.

## Estimation and false discovery control for the analysis of environmental mixtures

Srijata Samanta and Joseph Antonelli. Biostatistics, 2021.

## Multiple exposure distributed lag models with variable selection

Joseph Antonelli, Ander Wilson, and Brent Coull. Under revision. Biostatistics, 2021.

## The How and Why of Bayesian Nonparametric Causal Inference

Antonio Linero and Joseph Antonelli. WIREs Computational Statistics, 2022.

## Improved inference for doubly robust estimators of heterogeneous treatment effects

Heejun Shin and Joseph Antonelli. Under revision. Biometrics, 2022.

## Talk 1 on Relevant Topic in Your Field

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## Conference Proceeding talk 3 on Relevant Topic in Your Field

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## Teaching experience 1

Undergraduate course, University 1, Department, 2014

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## Teaching experience 2

Workshop, University 1, Department, 2015

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