University Research Professor M.Sc., PhD Western Ontario Office: HH-3054 Phone: (709) 864-8731 Fax: (709) 864-3010

Awards/Honors Received

• 1991 Elected Member of the International Statistical Institute
• 2004 University Research Professor
• 2004 International Institute of Forecasters and SAS Research award
• 2006 Who's who Canadian
• 2006 Fellow of the American Statistical Association
• 2007 Distinguished service award of the Statistical Society of Canada

Books/Articles/ Journal issues

• Dynamic Mixed Models for Familial Longitudinal Data (Springer Series in Statistics, February, 2011)
• GQL Inference (In Encyclopedia sponsored by 10 statistics societies, Springer)
• Multivariate t-Distribution (In Encyclopedia of Statistical Sciences, John Wiley)
• Inferences in GLLMMs (Special issue of the Canadian Journal of Statistics, 2010, June issue, John Wiley)

Selected Research Contributions

• Demonstrated that the so-called GEEs (generalized estimating equations) based regression estimates can be inefficient than simpler estimates [Sutradhar and Das (1999, Biometrika)].
• Introduced GQL (generalized quasi-likelihood) estimation approach for longitudinal data [Sutradhar (2003, Statistical Science)] as a generalization of the QL approach for independent data.
• Introduced GQL inferences in GLMMs (generalized linear mixed models) [Sutradhar (2004, Sankhya B)].
• Demonstrated that the GQL is a superior estimation approach than the so-called GMMs (generalized method of moments) estimation [Sutradhar, Rao and Pandit (2008, Sankhya B)] for panel data.
• Introduced FSMQL (fully standardized Mallow's type QL) approach for consistent regression estimation in GLMs with outliers [Bari and Sutradhar (2010, Scandinavian Journal of Statistics)].
• Demonstrated that the conditional inverse weights based GEE approach produces inconsistent estimates for GLLMs (generalized linear longitudinal models) subject to missing values [Sutradhar and Mallick (2010, Canadian Journal of Statistics)].
• Introduced GLLMMs [Sutradhar (2010, Canadian Journal of Statistics)].