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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Joseph Antonelli
Assistant Professor of Statistics
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Posts
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Blog Post number 1
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portfolio
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publications
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.
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. 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. Biometrics, 2022.
Heterogeneous causal effects of neighborhood policing in New York City with staggered adoption of the policy
Joseph Antonelli and Brenden Beck. Journal of the Royal Statistical Society: Series A, 2023.
Robust inference for geographic regression discontinuity designs: assessing the impact of police precincts
Emmett Kendall, Brenden Beck, and Joseph Antonelli. Journal of the Royal Statistical Society: Series A. Revision invited, 2023.
Principal stratification with continuous treatments and continuous post-treatment variables
Joseph Antonelli, Fabrizia Mealli, Brenden Beck, and Alessandra Mattei. ArXiv, 2023.
A spatial interference approach to account for mobility in air pollution studies with multivariate continuous treatments
Heejun Shin, Danielle Braun, Kezia Irene, Michelle Audirac, and Joseph Antonelli. Journal of the American Statistical Association, Revision invited, 2023.
Treatment Effect Heterogeneity and Importance Measures for Multivariate Continuous Treatments
Heejun Shin, Antonio Linero, Michelle Audirac, Kezia Irene, Danielle Braun, Joseph Antonelli. The Annals of Applied Statistics. Revision invited, 2024.
Autoregressive models for panel data causal inference with application to state-level opioid policies
Joseph Antonelli, Max Rubinstein, Denis Agniel, Rosanna Smart, Elizabeth Stuart, Matthew Cefalu, Terry Schell, Joshua Eagan, Elizabeth Stone, Max Griswold, Mark Sorbero, and Beth Ann Griffin. ArXiv, 2024.
Smooth and shape-constrained quantile distributed lag models
Yisen Jin, Aaron Molstad, Ander Wilson, and Joseph Antonelli. Biometrics. Revision invited, 2024.
Partial identification and unmeasured confounding with multiple treatments and multiple outcomes
Suyeon Kang, Alexander Franks, Michelle Audirac, Danielle Braun, and Joseph Antonelli. ArXiv, 2024.
talks
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
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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