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 ...

Bayesian methods furnish an attractive approach to inference in generalized linear mixed models. In the absence of subjective prior information for the random-effect variance components, these ...

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 ...

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 ...

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 ...