معرفی
David Todem is a Professor in the Department of Epidemiology and Biostatistics at Michigan State University. His work focuses on statistical methodology for longitudinal and clustered data, particularly in applications to cancer research and public health. He holds a Ph.D. in Statistics from the University of Wisconsin-Madison, an M.S. in Biostatistics from Hasselt University (Belgium), and an M.S. in Population Health from the University of Wisconsin-Madison.
Dr. Todem's research interests include joint models for time-to-event and longitudinal outcomes, non-identifiable models with informative nonresponse, and testing heterogeneity in mixture models. His applied work addresses critical questions in cancer treatment efficacy, maternal-child health, and chronic disease surveillance. He has developed innovative methods for analyzing quality-of-life outcomes in cancer patients and spatial epidemiology of co-infections.
Key contributions include the
- Validation of geospatial health indices
- Advancements in zero-inflated model testing
- Development of nonparametric scanning techniques
- Statistical frameworks for pediatric intervention evaluation
He received a prestigious National Cancer Institute K01 award and has collaborated on federally-funded programs improving cardiovascular care in underserved populations. His work spans multiple domains including maternal-fetal medicine, environmental health, and global health equity.
Methodological strengths include:
- Handling non-random missing data
- High-dimensional feature selection
- Weakly identifiable model sensitivity analysis
Current research emphasizes translating statistical innovations into clinical practice through partnerships with healthcare systems and public health agencies.
