Please Enter a Search Term

Brajendra Sutradhar

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

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)].
  • List of Research Publications.

Other Research Interests

Multivariate Analysis; Time Series Analysis; Sampling; Correlated Failure Time Data Analysis; Spatial-Temporal Data Analysis;Wavelets in Statistics.

Selected Professional Services

General Chair (ISS 2009, ISS 2012); Local arrangements Chair for SSC annual meetings (SSC 1990, SSC 2007); Member of NSERC grants selection committee (1992, 1997-2000); Program Chair for the Annual Meeting of Statistical Society of Canada (SSC 1997); Associate Editor of Canadian Journal of Statistics (1995-1997, 2004-2006); Program Secretary of Statistical Society of Canada (2002-2005); Member of Statistics Canada Advisory Committee on Statistical Methods (2001-2003); Associate Editor of Journal of Environmental and Ecological Statistics (2004-08).

Teaching Interest

All areas of Theoretical and Applied Statistics.

Thesis Supervised

Ph.D. Thesis:

  • Sun, Bingrui (November 2013). Bivariate Multinomial Models.
  • Warriyar K. V., Vineetha (February 2013). Generalized linear longitudinal semi-parametric models with time dependent covariates.
  • Hubert, M. H. (December 2012). Family based spatial correlation models.
  • Chowdhury, Rafiqul (October 2011). Inferences in longitudinal multinomial fixed and mixed models.
  • Tagore, Vickneswary (October 2010). Inferences in volatility models.
  • Mallick, Taslim (August 2009). Conditional weighted generalized quasi-likelihood inferences in incomplete longitudinal models for binary and count data.
  • Bari, Wasimul (October 2007). Robust estimation in familial and longitudinal models.
  • Hasan, Tariqul (December 2004). Analyzing correlated failure time data.
  • Vandna Jowaheer (December 2000). Analysing multivariate longitudinal count data.

M.Sc./MAS Thesis:

  • Zheng, Nan (August 2013). Inference in stochastic volatility models for Gaussian and t data.
  • Wooden, Tracey (June 2013). Inferences in non-stationary longitudinal binary models.
  • Nagarajah, Varathan (December 2012). Median regression for asymmetric longitudinal data: A quasi-Likelihood approach.
  • Sun, Bingrui (August 2009). GQL inferences in linear mixed models with dynamic mean structure.
  • Granter, Lauren (October 2007). Complex sampling design based inference on familial models for count data.
  • Chowdhury, Rafiqul (September 2007). Generalized quasi-likelihood versus hierarchical likelihood inferences in generalized linear mixed models for count data.
  • Madan, Manish (October 2006). Quasilikelihood inferences in gamma AR(1) models for longitudinal data.
  • Tagore, Vickneswary (August 2006). Analyzing binary time series.
  • Mallick, Taslim (September 2004). Observation-driven regression models for time series of counts.
  • Braimoh, Adebola (January 2004). Analysing longitudinal data in the presence of missing responses with application to SLID data.
  • Bari, Wasimul (September 2003). Analyzing binary longitudinal data from adaptive clinical trials: A generalized quasilikelihood approach.
  • Gwenda Drover (May 2002). Tests for longitudinal change in skewed samples with application to Hibernia sediment chemistry.
  • Rajendra Neupane (June 2002). Regression analysis for longitudinal hemoglobin data from premature infants with outcomes subject to non-response.
  • Tariqul Hasan (June 2001). Analyzing longitudinally correlated failure time data: A generalized estimating equation approach.
  • Dennis Batten (January 2000). Univariate polytomous ordinal regression analysis with application to diabetic retinopathy data.
  • Santosh Sutradhar (August 1998). On classification of bivariate binary observations.
  • Maxwell Hoyles (December 1998). Longitudinal and gestational effects of minerals in human milk.
  • Krishna Saha (July 1996). On the distribution of order statistics from unequally correlated normal variables: A small correlations approach.
  • Zhende Qu (January 1995). On approximate likelihood inference in the Poisson mixed model.
  • Md. Baki Billah (July 1995). The analysis of multivariate failure time data.
  • Glen Luther (May 1989). Use of morphometric character to identify North American and European stocks of Atlantic salmon.
  • M. A. Azam (December 1988). Modelling factors affecting relative performance of two dust samplers in Labrador mines.
Share