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https://hdl.handle.net/1959.11/6974
Title: | A Comparison of Methods for Analysing Correlated Count Data | Contributor(s): | Alston, Clair (author); Murison, Robert (supervisor); Smith, David (supervisor) | Conferred Date: | 1998 | Copyright Date: | 1997 | Open Access: | Yes | Handle Link: | https://hdl.handle.net/1959.11/6974 | Abstract: | This thesis considers extensions of Generalized Linear Models (Nelder and Wedderburn, 1972) to incorporate correlated count data. Of particular interest is the Poisson random effects model which is commonly solved by approximate methods due to the complexity of calculations in maximum likelihood estimation (Diggle, Liang and Zeger, 1994, pl73-5). The methods considered fall into 4 categories; 1. quasi-likelihood techniques, (Schall, 1991), (Breslow and Clayton, 1993), 2. overdispersion models, (Van de Ven and Weber, 1995) 3. generalized estimating equations, (Liang and Zeger, 1986), and 4. Markov Chain Monte Carlo techniques, (Zeger and Karim, 1991). | Publication Type: | Thesis Masters Research | Rights Statement: | Copyright 1997 - Clair Alston | HERDC Category Description: | T1 Thesis - Masters Degree by Research |
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Appears in Collections: | Thesis Masters Research |
Files in This Item:
File | Description | Size | Format | |
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open/SOURCE03.pdf | Abstract | 552.32 kB | Adobe PDF Download Adobe | View/Open |
open/SOURCE04.pdf | Thesis | 3.39 MB | Adobe PDF Download Adobe | View/Open |
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