Generalized linear mixed model analysis using quasi-likelihood

Lambert, Amanda (2007) Generalized linear mixed model analysis using quasi-likelihood. Masters thesis, Memorial University of Newfoundland.

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Abstract

When investigating the relationship between two or more variables, regression is a commonly used method of analysis. Linear regression, in particular, is used when the expected value of the response is a linear function of the explanatory variables. If it is not a linear function, generalized linear regression is used. Furthermore, when the data is not independent, mixed models are used. There are various ways to analyze linear mixed models and generalized linear mixed models. In this thesis, we focus on the moment method of analysis, simulated approaches and the quasi-likelihood method of analysis. Analysis is conducted on simulated data for a linear mixed model, simulated data for a generalized linear mixed model and on a real data, set. The real data set is a clustered data set of the number of times a person visits a physician in a given year.

Item Type: Thesis (Masters)
URI: http://research.library.mun.ca/id/eprint/9165
Item ID: 9165
Additional Information: Includes bibliographical references (leaves 92-93)
Department(s): Science, Faculty of > Mathematics and Statistics
Date: 2007
Date Type: Submission
Library of Congress Subject Heading: Estimation theory; Linear models (Statistics); Regression analysis

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