Document Type
Article
Publication Date
12-15-2008
Journal / Book Title
Computational Statistics & Data Analysis
Abstract
In practical data analysis, nonresponse phenomenon frequently occurs. In this paper, we propose an empirical likelihood based confidence interval for a common mean by combining the imputed data, assuming that data are missing completely at random. Simulation studies show that such confidence intervals perform well, even when the missing proportion is high. Our method is applied to an analysis of a real data set from an AIDS clinic trial study.
DOI
10.1016/j.csda.2008.09.021
MSU Digital Commons Citation
Liang, Hua; Su, Haiyan; and Zou, Guohua, "Confidence Intervals for a Common Mean with Missing Data with Applications in an AIDS Study" (2008). Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works. 32.
https://digitalcommons.montclair.edu/appliedmath-stats-facpubs/32