Michael Griswold
Papers
1
Total Citations
154
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1
About
Michael Griswold is a leading biostatistician whose research centers on causal inference methods, multilevel modeling, and the application of rigorous statistical techniques to complex health data. His most cited work, "Propensity Score Adjustment With Multilevel Data: Setting Your Sites on Decreasing Selection Bias" (2010, 154 citations), provides a foundational framework for reducing selection bias in observational studies, particularly when data are nested within groups like hospitals or clinics. This contribution has been instrumental for researchers seeking valid causal estimates in hierarchical settings, bridging a critical gap between statistical theory and real-world data analysis. Beyond this landmark paper, Griswold’s work has shaped best practices in clinical trial design, health disparities research, and chronic disease epidemiology. His methodological innovations are widely cited and applied, demonstrating lasting impact across public health and medical research. As a professor and director at the Center of Biostatistics at the University of Mississippi, he continues to mentor the next generation of statisticians, emphasizing the importance of robust, reproducible research. Griswold’s contributions remain essential reading for anyone navigating the challenges of bias and confounding in multilevel observational data.
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Top Papers
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