A moving blocks empirical likelihood method for longitudinal data

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A moving blocks empirical likelihood method for longitudinal data

TitleA moving blocks empirical likelihood method for longitudinal data
Publication TypeJournal Article
Year of Publication2015
AuthorsQiu, J, WU, LANG
JournalBiometrics
Volume71
Pagination616–624
Date Publishedsep
ISSN1541-0420
KeywordsEmpirical likelihood, General estimating equation, Longitudinal data, Nonparametric method, Serial correlation
AbstractIn the analysis of longitudinal or panel data, neglecting the serial correlations among the repeated measurements within subjects may lead to inefficient inference. In particular, when the number of repeated measurements is large, it may be desirable to model the serial correlations more generally. An appealing approach is to accommodate the serial correlations nonparametrically. In this article, we propose a moving blocks empirical likelihood method for general estimating equations. Asymptotic results are derived under sequential limits. Simulation studies are conducted to investigate the finite sample performances of the proposed methods and compare them with the elementwise and subject-wise empirical likelihood methods of Wang et al. (2010, Biometrika 97, 79–93) and the block empirical likelihood method of You et al. (2006, Can. J. Statist. 34, 79–96). An application to an AIDS longitudinal study is presented.
URLhttp://onlinelibrary.wiley.com/doi/10.1111/biom.12317/abstract
DOI10.1111/biom.12317