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 ...

The method of maximum likelihood (ML) is widely used for analyzing generalized linear mixed models (GLMM's). A full maximum likelihood analysis requires numerical integration techniques for ...

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), ...

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 or discrete ...

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 ...

Generalized Linear Models Generalized Linear Models Course Topics Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, ...

The mixed model is written as where everything is the same as in the general linear model except for the addition of the known design matrix, Z, and the vector of unknown random-effects parameters,.