معرفی
James Stamey serves as Chairman and Professor of Statistical Science at Baylor University in Waco, Texas, holding a leadership role within his academic unit while maintaining active research and teaching responsibilities.
His research centers on Bayesian statistical methodologies with specialized focus on data imperfections including misclassification, underreporting, and unmeasured confounding. He has developed innovative approaches for sample size determination in cost-effectiveness studies, diagnostic test evaluation, and clinical trial design. His work bridges theoretical statistics with practical applications in epidemiology, public health surveillance, and evidence-based medicine, addressing critical challenges in real-world data analysis such as correcting misreported COVID-19 counts and modeling hospital admission risks.
Analysis of his recent publications (2021-2025) reveals consistent methodological innovation in Bayesian computation and sensitivity analysis. His work demonstrates increasing emphasis on developing practical tools (like the unmconf R package) for real-world evidence generation, with applications spanning physical activity assessment, schizophrenia-related hospitalizations, and pharmaceutical statistics. The publications show strong integration of spatial modeling, hierarchical structures, and meta-analytic techniques to address data limitations in observational studies.
