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School of Public Health
Department: Epidemiology and Biostatistics
Analysis of multivariate incomplete data; multilevel models; Bayesian data analysis; computational statistics and response error problems
Campus phone: (518) 402-0421
Campus email: firstname.lastname@example.org
Recai Yucel's research is motivated by methodological issues in health services research and prevention research. Specifically, his work focuses on computational algorithms and software development, hierarchical and latent variable models, models and methods for response errors and applied Bayesian statistics.
Yucel has worked with investigators at the Methodology Center at Pennsylvania State University to develop a statistical methodology for analyzing incomplete multivariate multilevel data.
He was awarded a fellowship by the American Statistical Association and the National Center for Health Statistics to develop and disseminate methods for handling item nonresponse in complex sample surveys.