
About
Michael R. Elliott is a Professor of Biostatistics at the University of Michigan School of Public Health and a Research Professor at the Institute for Social Research, specializing in statistical methodology for public health applications including women's health, child development, and tobacco control.
His academic credentials include:
- PhD in Biostatistics from the University of Michigan (1999)
- MS in Biostatistics from the University of Michigan (1997)
- BA from the University of Chicago (1985)
Dr. Elliott's research pioneers advanced techniques for missing data analysis, causal inference, and survey methodology. He develops Bayesian approaches for complex sample surveys, methods for combining probability and non-probability samples, and frameworks for assessing surrogate markers in clinical trials. His work bridges theoretical statistics with collaborative projects in injury prevention, pediatrics, and social determinants of health.
Analysis of his recent publications reveals consistent application of missing data and causal inference methods to pressing public health issues: women's health (menopause transitions, child development via ECHO), substance use (tobacco/cannabis policy impacts), and social epidemiology (discrimination, neighborhood effects). Methodologically, his work emphasizes Bayesian modeling, latent variable structures, and rigorous survey design.
As lead biostatistician for the NIH-funded ECHO Michigan cohort, he directs statistical strategy for national child health research. He maintains active collaborations with the Institute for Social Research on environmental health determinants and the University of Michigan Transportation Research Institute on driver safety analytics, leveraging naturalistic driving data.
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