Series of Departmental seminars
Friday 11 January | 12:00
Maths & Physics Building, Lab Room 602
By Prof. Liberato Camilleri
Generalized linear mixed models (GLMM) are extensions to Generalized linear models (GLM) in which the linear predictor contains random effects in addition to the usual fixed effects. Multilevel models are GLMM and are used to analyse hierarchical structured data where observations are nested within higher levels of classification.
In these models, processes occurring at a higher level of analysis influence the characteristics and processes occurring at a lower level. In this presentation, we will discuss random intercept and random coefficient models, intraclass correlation, maximum likelihood estimation, adaptive quadrature, empirical Bayes prediction and other estimation methods. Several applications related to education and SEBD will be presented to illustrate the methodologies.