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Trangucci, Rob

Rob Trangucci

Assistant Professor
Department of Statistics

Rob Trangucci

Assistant Professor
Department of Statistics


My research focuses on developing novel statistical methodology in missing data analysis and causal inference for problems in epidemiology, designing Bayesian methods for survey inference, and creating tools to quantify how priors impact posterior inferences. Before I returned to academia to pursue a doctorate in statistics, I worked as a data scientist for a fintech startup, a statistical consultant for a Big Five publisher, and a core developer for the Stan statistical modeling and inference platform ( I earned a PhD in Statistics from the University of Michigan, an M.A. in Quantitative Methods in the Social Sciences from Columbia University, and a B.A. in Physics from Bucknell University.


Research Interests

  • Causal inference for vaccine efficacy
  • Missing data
  • Principal stratification
  • Prior influence
  • Multilevel regression and poststratification (MRP)
  • Bayesian inference


Ph.D. in Statistics, University of Michigan 2023

M.A. in Quantitative Methods in the Social Sciences, Columbia University 2014

B.A. in Physics, Bucknell University, 2009


  • Rob Trangucci, Yang Chen, Jon Zelner (2022). Modeling racial/ethnic differences in COVID-19 incidence with covariates subject to non-random missingness. Accepted at Annals of Applied Statistics.
  • Jon Zelner, Rob Trangucci, Ramya Naraharisetti, Alex Cao, Ryan Malosh, Kelly Broen, Nina Masters, Paul Delamater (2021). Racial Disparities in Coronavirus Disease 2019 (COVID-19) Mortality Are Driven by Unequal Infection Risks. Clinical Infectious Diseases.
  • David E. Jones, Rob Trangucci, Yang Chen (2021). Quantifying Observed Prior Impact. Bayesian Analysis.
  • Yajuan Si, Rob Trangucci, Jonah Sol Gabry, Andrew Gelman (2020). Bayesian Hierarchical Weighting Adjustment and Survey Inference. Survey Methodology..
  • Jesse D. Contreras, Rob Trangucci, Eunice E. Felix-Arellano, Sandra Rodríguez-Dozal, Christina Siebe, Horacio Riojas-Rodr\ǵuez, Rafael Meza, Jon Zelner, Joseph N.S. Eisenberg (2020). Modeling Spatial Risk of Diarrheal Disease Associated with Household Proximity to Untreated Wastewater Used for Irrigation in the Mezquital Valley, Mexico. Environmental Health Perspectives.
  • Jon Zelner, Joshua G. Petrie, Rob Trangucci, Emily T. Martin, Arnold S. Monto (2019). Effects of Sequential Influenza A(H1N1)Pdm09 Vaccination on Antibody Waning. The Journal of Infectious Diseases.