|
Research Overview
My research area includes, statistical methodology and applications involving categorical and longitudinal data, classification and clustering, spatio-temporal and survival data analysis and modeling extreme events. My areas of his research applications include Biometry, Bioinformatics, Data mining, Environmetrics, Morphometry, and Population Genetics. My research was supported by various grants from NIH and DOD. My current research includes modeling multiple cancer survival data with cure rate modeling in presence of spatial components with applications in SEER data base from National Cancer Institute. I have also funding from NIH on biomarker identification from genomic sequence data. My present research will be extremely useful for various clinical and translational research.
Education
Ph.D. Purdue University, 1980, Statistics
M.S. Purdue University, 1977, Statistics
B.Stat. Indian Statistical Institute, 1974, Statistics
Featured Publications
• Diva, U., D. Dey, and S. Banerjee. 2007. Modeling spatially correlated survival data for individuals with multiple cancers. Statistical Modeling 7:191-213.
• Banerjee, T., D. Dey, M.H. Chen, and S. Kim. 2007. Bayesian analysis of generalized odds-rate hazards models for survival data. Life Time Data Analysis 13:241-261.
• Liu, J. and D. Dey. 2007. Hierarchical overdispersed Poisson model with macrolevel autocorrelation. Statistical Methodology 4:354-370.
• Song, S., D. Dey, and K. Holsinger. 2006. Differentiation among populations with migration, mutation, and drift implications for genetic inference. Evolution 60:1-12.
• Fu, R., D. Dey, and K. Holsinger. 2005. Bayesian inference of population structure from dominant markers from mixtures of Betas. Bioinformatics 21:1516-1529.
• Kim, S., M.H. Chen, and D. Dey. 2008. Flexible generalized t-link models for binary response data. Biometrika 95:93-106.
• Chen, M.H., D. Dey, and J. Ibrahim. 2004. Bayesian criterion based model assessment for categorical data. Biometrika 91:45-63.
• Holsinger., K., P. Lewis, and D. Dey. 2002. A Bayesian approach to inferring population structure from dominant markers. Molecular Ecology 11:1157-1164.
• Chen, M.H., D. Dey, and Q.M. Shao. 1999. A new skewed link model for dichotomous quantal response data. Journal of the American Statistical Association 94:1172-1186
• Sinha, D., and D. Dey. 1997. Semi parametric Bayesian analysis of survival data. Journal of the American Statistical Association 92:1195-1212.
|
