Confidence intervals for a common mean with missing data with applications in an AIDS study

Hua Liang, Haiyan Su, Guohua Zou

Research output: Contribution to journalArticleResearchpeer-review

6 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)546-553
Number of pages8
JournalComputational Statistics and Data Analysis
Volume53
Issue number2
DOIs
StatePublished - 15 Dec 2008

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Common Mean
Missing Data
Confidence interval
Missing Completely at Random
Non-response
Empirical Likelihood
Data analysis
Proportion
Simulation Study

Cite this

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Confidence intervals for a common mean with missing data with applications in an AIDS study. / Liang, Hua; Su, Haiyan; Zou, Guohua.

In: Computational Statistics and Data Analysis, Vol. 53, No. 2, 15.12.2008, p. 546-553.

Research output: Contribution to journalArticleResearchpeer-review

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