Generalized linear mixed models are used to model clustered and longitudinal data in which the distribution of the response variable is a member of the exponential family. This thesis introduces a novel method for simultaneous clustering of such data and estimation of parameters of the underlying generalized linear mixed models.Clustering has been extensively studied for both cross-sectional and longitudinal data. In longitudinal data, one has to take into account the association between observations taken on the same individual. This has found applications in epidemiology, genetics, biology, market research, economics, and many other areas.Generalized linear mixed models consist of two sets of parameters: fixed ef-iv Table of Contents v List of Tables x List of Figures xii List of Tables 2.1 Common distributions in exponential family of distributions . . . . . 14
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