Linear mixed model (LMM) methodology is a powerful technology to analyze models containing both the fixed and random effects. The model was first proposed to estimate genetic parameters for ...

Sanjoy K. Sinha, Robust Analysis of Generalized Linear Mixed Models, Journal of the American Statistical Association, Vol. 99, No. 466 (Apr., 2004), pp. 451-460 ...

Sanjoy K. SINHA, Bootstrap tests for variance components in generalized linear mixed models, The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 37, No. 2 (June/juin 2009), ...

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Course Topics Ordinary linear regression (OLR) assumes that response variables are continuous. Generalized Linear Models (GLMs) provide an extension to OLR since response variables can be continuous ...

Since 1987, MCEER, formerly the Multidisciplinary Center for Earthquake Engineering Research (MCEER) and the National Center for Earthquake Engineering Research ( NCEER), has produced over 600 ...