| Estimating the causal effect of low levels of fine particulate matter on hospitalization M Makar, J Antonelli, Q Di, D Cutler, J Schwartz, F Dominici Epidemiology 28 (5), 627-634, 2017 | 97 | 2017 |
| Statistical workflow for feature selection in human metabolomics data J Antonelli, BL Claggett, M Henglin, A Kim, G Ovsak, N Kim, K Deng, ... Metabolites 9 (7), 143, 2019 | 76 | 2019 |
| Doubly robust matching estimators for high dimensional confounding adjustment J Antonelli, M Cefalu, N Palmer, D Agniel Biometrics 74 (4), 1171-1179, 2018 | 59 | 2018 |
| Spike-and-slab group lassos for grouped regression and sparse generalized additive models R Bai, GE Moran, JL Antonelli, Y Chen, MR Boland Journal of the American Statistical Association 117 (537), 184-197, 2022 | 52 | 2022 |
| Parental language input to children with hearing loss: Does it matter in the end? S Nittrouer, JH Lowenstein, J Antonelli Journal of Speech, Language, and Hearing Research 63 (1), 234-258, 2020 | 37 | 2020 |
| High-dimensional confounding adjustment using continuous spike and slab priors J Antonelli, G Parmigiani, F Dominici Bayesian analysis 14 (3), 805, 2019 | 36 | 2019 |
| Causal inference in high dimensions: a marriage between Bayesian modeling and good frequentist properties J Antonelli, G Papadogeorgou, F Dominici Biometrics 78 (1), 100-114, 2022 | 34* | 2022 |
| Estimating the health effects of environmental mixtures using Bayesian semiparametric regression and sparsity inducing priors J Antonelli, M Mazumdar, D Bellinger, D Christiani, R Wright, B Coull | 31 | 2020 |
| Guided Bayesian imputation to adjust for confounding when combining heterogeneous data sources in comparative effectiveness research J Antonelli, C Zigler, F Dominici Biostatistics 18 (3), 553-568, 2017 | 21 | 2017 |
| Mitigating bias in generalized linear mixed models: The case for Bayesian nonparametrics J Antonelli, L Trippa, S Haneuse Statistical science: a review journal of the Institute of Mathematical …, 2016 | 15 | 2016 |
| A single visualization technique for displaying multiple metabolite–phenotype associations M Henglin, T Niiranen, JD Watrous, KA Lagerborg, J Antonelli, ... Metabolites 9 (7), 128, 2019 | 14 | 2019 |
| Heterogeneous causal effects of neighbourhood policing in New York City with staggered adoption of the policy J Antonelli, B Beck Journal of the Royal Statistical Society Series A: Statistics in Society 186 …, 2023 | 12* | 2023 |
| The how and why of Bayesian nonparametric causal inference AR Linero, JL Antonelli Wiley Interdisciplinary Reviews: Computational Statistics 15 (1), e1583, 2023 | 12 | 2023 |
| Quantitative comparison of statistical methods for analyzing human metabolomics data M Henglin, BL Claggett, J Antonelli, M Alotaibi, GA Magalang, JD Watrous, ... Metabolites 12 (6), 519, 2022 | 11 | 2022 |
| Multiple exposure distributed lag models with variable selection J Antonelli, A Wilson, BA Coull Biostatistics 25 (1), 1-19, 2024 | 8 | 2024 |
| Averaging causal estimators in high dimensions J Antonelli, M Cefalu Journal of Causal Inference 8 (1), 92-107, 2020 | 8 | 2020 |
| Spatial multiresolution analysis of the effect of PM2. 5 on birth weights J Antonelli, J Schwartz, I Kloog, BA Coull The annals of applied statistics 11 (2), 792, 2017 | 8 | 2017 |
| The positive effects of population-based preferential sampling in environmental epidemiology J Antonelli, M Cefalu, L Bornn Biostatistics 17 (4), 764-778, 2016 | 7 | 2016 |
| All models are wrong, but which are useful? Comparing parametric and nonparametric estimation of causal effects in finite samples KE Rudolph, NT Williams, CH Miles, J Antonelli, I Diaz Journal of Causal Inference 11 (1), 20230022, 2023 | 6 | 2023 |
| Statistical Workflow for Feature Selection in Human Metabolomics Data. Metabolites. 9, 143 J Antonelli, BL Claggett, M Henglin, A Kim, G Ovsak, N Kim, K Deng, ... | 6 | 2019 |
