Type of Document Master's Thesis Author Lin, Wei-Lun Author's Email Address wlin6@student.gsu.edu URN etd-11272007-193524 Title SELECTING THE WORKING CORRELATION STRUCTURE BY A NEW GENERALIZED AIC INDEX FOR LONGITUDINAL DATA Degree Master of Science Department Mathematics and Statistics Advisory Committee
Advisor Name Title Jiawei Liu Committee Chair Keywords
- Longitudinal data
- Generalized AIC Index
- Working Correlation
- Generalized Estimating Equation
Date of Defense 2007-11-19 Availability unrestricted Abstract The analysis of longitudinal data has been a popular subject for the recent years. The growth of the Generalized Estimating Equation (GEE) Liang & Zeger, 1986) is one of the most influential recent developments in statistical practice for this practice. GEE methods are attractive both from a theoretical and a practical standpoint. In this paper, we are interested in the influence of different "working" correlation structures for modeling the longitudinal data. Furthermore, we propose a new AIC-like method for the model assessment which generalized AIC from the point of view of the data generating. By comparing the difference of the log-likelihood functions between different correlation models, we define the exact value to create an interval for our model selection. In this thesis, we combine the GEE method and a new generalized AIC Index for the longitudinal data with different correlation structures.Files
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