Charlotte Zilber Mann

Charlotte Zilber Mann

Statistics PhD Candidate

University of Michigan

I am a fifth year PhD candidate in the Department of Statistics at the University of Michigan, supervised by Johann Gagnon-Bartsch. My work bridges the gap between the causal analyses a researcher would like to do and the data that they actually have.

I am interested in ways that various data sources can be combined for casual inference to leverage the strengths of each source, while mitigating any limitations. I currently work on improved estimation by combining observational data and data from randomized controlled trials, precise estimators for paired cluster randomized trials, and data fusion for causal inference when data privacy is a concern. I have also worked with Ben B. Hansen on specialized propensity score matching methods for observational study design and design-based inference that accommodates censored outcomes.

My interests are driven by a desire to do research with applications in education and public health. Within these broad fields, I am interested in educational interventions, pedagogy, equity in education, social determinants of health, and equity in health care access.

I am also committed to improving as an instructor and am interested in Statistics pedagogy, with particular interest in improving instruction of introductory statistics courses.

Interests

  • Causal Inference
  • Education and Pedagogy
  • Randomized Controlled Trials

Education

  • PhD in Statistics (expected), 2024

    University of Michigan

  • MA in Statistics, 2021

    University of Michigan

  • BA in Mathematics with a Statistics Track, 2017

    Carleton College

Publications

Combining observational and experimental data for causal inference considering data privacy

Combining observational and experimental data for causal inference can improve treatment effect estimation. However, many observational …

Derivation and external validation of a simple risk score to predict in-hospital mortality in patients hospitalized for COVID-19

As severe acute respiratory syndrome coronavirus 2 continues to spread, easy-to-use risk models that predict hospital mortality can …

Protocol -- Evaluating the effect of ACA Medicaid expansion on mortality during the COVID-19 pandemic using county level matching

States are able to choose whether to expand Medicaid as part of the Affordable Care Act (ACA); thus it is of interest to understand the …

Protocol: Evaluating the Effect of ACA Medicaid Expansion on 2015-2018 Mortality Through Matching and Weighting

Starting in 2014, states received the option to expand Medicaid through the Affordable Care Act (ACA). Many states chose to expand …

Experience

 
 
 
 
 

Graduate Student Instructor

University of Michigan

Sep 2019 – Present Ann Arbor, MI
 
 
 
 
 

Senior Analyst

Analysis Group

Aug 2017 – Jul 2019 Boston, MA

Analyst (August 2017 – December 2018)

Intern Analyst (June 2016 - August 2016)

Contributed to the creation and support of data-driven arguments in anti-trust and consumer survey cases.

 
 
 
 
 

Undergraduate Researcher

UMBC HPC REU

Jun 2015 – Aug 2015 Baltimore, Maryland
Collaborated with three undergraduates, a graduate student, and faculty mentor to complete a 6-week research project, poster, and technical report for client Amita Mehta at the Joint Center for Earth Systems Technology. Completed a short course in high performance computing.
 
 
 
 
 

Research Assistant

Iowa State University

Jun 2014 – Aug 2014 Ames, Iowa
Worked with Dr. Ulrike Genschel on NSF funded research “Exploring the STEM Gender Gap” (award 1036791).