Date of Award
6-9-2006
Degree Type
Closed Thesis
Degree Name
Master of Science (MS)
Department
Mathematics and Statistics
First Advisor
Yichuan Zhao - Chair
Second Advisor
Yu-Sheng Hsu
Third Advisor
Pulak Ghosh
Fourth Advisor
Jun Han
Abstract
The case-control studies are primary tools for the study of risk factors (exposures) related to the disease interested. The case-control studies using longitudinal data are cost and time efficient when the disease is rare and assessing the exposure level of risk factors is difficult. Instead of GEE method, the method of using a prospective logistic model for analyzing case-control longitudinal data was proposed and the semiparametric inference procedure was explored by Park and Kim (2004). In this thesis, we apply an empirical likelihood ratio method to derive limiting distribution of the empirical likelihood ratio and find one likelihood-ratio based confidence region for the unknown regression parameters. Our approach does not require estimating the covariance matrices of the parameters. Moreover, the proposed confidence region is adapted to the data set and not necessarily symmetric. Thus, it reflects the nature of the underlying data and hence gives a more representative way to make inferences about the parameter of interest. We compare empirical likelihood method with normal approximation based method, simulation results show that the proposed empirical likelihood ratio method performs well in terms of coverage probability.
DOI
https://doi.org/10.57709/1059664
Recommended Citation
Jian, Wen, "Analysis of Longitudinal Data in the Case-Control Studies via Empirical Likelihood." Thesis, Georgia State University, 2006.
doi: https://doi.org/10.57709/1059664