Michael R. Elliott

Department of Biostatistics
University of Michigan School of Public Health
M4041, SPH II
1420 Washington Heights
Ann Arbor, MI 48105
Voice: (734) 647-5160 Fax: (734) 763-2215

Survey Methodology Program
Institute for Social Research
Rm 4065, 426 Thompson St.
Ann Arbor, MI 48106
Voice: (734) 647-5563 Fax: (734) 764-8263

Welcome to Michael Elliott's homepage. I am an associate professor in the Department of Biostatistics at the University of Michigan School of Public Health, and an associate research professor at the Institute for Social Research. Below find links to classes that I teach, my current research interests, and useful or amusing Web links.   Back to SPH bio page.

Email me: mrelliot@umich.edu

Research Interests

Statistical Methodology

Collaborative Research

My collaborative research interests have been organized to some degree around injury control. Partners in Child Passenger Safety uses a known-probability sample of children in accidents involving claims to State Farm Insurance Companies to investigate child occupant protection in vehicular crashes. (Profiled in the University of Michigan School of Public Health Findings magazine.)

The Social and Behavioral Analysis Division of the University of Michigan Transportation Research Institute conducts research that advances understanding of the social and behavioral issues important to transportation, including developing and testing intervention programs that promote safe driving, expanding the knowledge of social and behavioral factors related to high-risk driving behavior, and understanding the relationship between public policy and social and behavioral factors in transportation.

Collaboration with Wharton Risk Management and Decision Processes Center focuses on the analysis of the RMP*Info database, which includes the safety record from 1994-2005 of over 15,000 industrial facilities using above-threshold quantities of 77 toxic or 66 flammable chemicals.

The Philadelphia Gun and Alcohol Study is a major case-control study assessing the impact of alcohol outlets on risk of firearms injury. The study uses novel recruiting strategies that attempt to map cases and control into a spatial-temporal pattern to assess risk of injury after adjusting for confounding due to alcohol outlets being located in business districts with high traffic volumes.

Datasets and other materials for classes are here:

S-Plus Introduction:
  • Presentation
  • Code examples
  • Bootstrapping exercise
  • Bootstrapping code

  • Missing Data Lectures at the Advanced School and Conference on Statistics and Applied Probability in the Life
    Sciences at the Abdus Salam Institute for Theoretical Physics, Trieste, Italy:
    Handling Missing Data in Statistical Analyses