Semi-empirical likelihood confidence intervals for the differences of quantiles with missing data

Detecting population (group) differences is useful in many applications, such as medical research. In this paper, we explore the probabilistic theory for identifying the quantile differences between two populations. Suppose that there are two populations x and y with missing data on both of them, wh...

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Bibliographic Details
Published inActa mathematica Sinica. English series Vol. 25; no. 5; pp. 845 - 854
Main Authors Qin, Yong Song, Zhang, Jun Chao
Format Journal Article
LanguageEnglish
Published Heidelberg Institute of Mathematics, Chinese Academy of Sciences and Chinese Mathematical Society 01.05.2009
Springer Nature B.V
Subjects
Algebraic group theory
Mathematics
Mathematics and Statistics
Methods
Missing data
Studies
Survival analysis
62G05
empirical likelihood
quantile
62E20
confidence interval
hot deck imputation
missing data
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Summary:Detecting population (group) differences is useful in many applications, such as medical research. In this paper, we explore the probabilistic theory for identifying the quantile differences between two populations. Suppose that there are two populations x and y with missing data on both of them, where x is nonparametric and y is parametric. We are interested in constructing confidence intervals on the quantile differences of x and y . Random hot deck imputation is used to fill in missing data. Semi-empirical likelihood confidence intervals on the differences are constructed.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1439-8516
1439-7617
DOI:10.1007/s10114-009-6476-5