Date of Award
5-9-2015
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Mathematics and Statistics
First Advisor
Yichuan Zhao
Second Advisor
Jing Zhang
Third Advisor
Xin Qi
Abstract
The use of doubly robust estimators is a key for estimating the population mean response in the presence of incomplete data. Cao et al. (2009) proposed an alternative doubly robust estimator which exhibits strong performance compared to existing estimation methods. In this thesis, we apply the jackknife empirical likelihood, the jackknife empirical likelihood with nuisance parameters, the profile empirical likelihood, and an empirical likelihood method based on the influence function to make an inference for the population mean. We use these methods to construct confidence intervals for the population mean, and compare the coverage probabilities and interval lengths using both the ``usual'' doubly robust estimator and the alternative estimator proposed by Cao et al. (2009). An extensive simulation study is carried out to compare the different methods. Finally, the proposed methods are applied to two real data sets.
DOI
https://doi.org/10.57709/7027239
Recommended Citation
Valdovinos Alvarez, Jose Manuel, "Empirical Likelihood Confidence Intervals for the Population Mean Based on Incomplete Data." Thesis, Georgia State University, 2015.
doi: https://doi.org/10.57709/7027239