Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/21238

Title: Modeling Hierarchical Data, Allowing for Overdispersion and Zero Inflation, in Particular Excess Zeros
Authors: Kassahun, Wondwosen
Advisors: Molenberghs, Geert
Faes, Christel
Issue Date: 2014
Abstract: In a lot of applied research, binary and count outcome frequently appear, next to continuous data. Statistical modeling of such data lies within the framework of exponential family distributions (McCullagh and Nelder, 1989; Agresti, 2002; Molenberghs and Verbeke, 2005). The resulting generalized linear models (GLMs) contain three components: a random component that identifies a vector of observations of the outcome and its probability distribution; a systematic component, i.e., a specification for the mean vector in terms of a vector of fixed unknown parameters and known covariate values; and a link function which specifies the function of expectation that the model equates to the systematic component with known link functions, such as the logit and log functions for binary and count data, respectively. ...
URI: http://hdl.handle.net/1942/21238
Category: T1
Type: Theses and Dissertations
Appears in Collections: PhD theses
Research publications

Files in This Item:

Description SizeFormat
N/A2.12 MBAdobe PDF

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.