Smooth bootstrap methods for analysis of longitudinal data

Li, Yue and Wang, You-Gan (2008) Smooth bootstrap methods for analysis of longitudinal data. Statistics In Medicine, 27 7: 937-953. doi:10.1002/sim.3027


Author Li, Yue
Wang, You-Gan
Title Smooth bootstrap methods for analysis of longitudinal data
Journal name Statistics In Medicine   Check publisher's open access policy
ISSN 0277-6715
1097-0258
Publication date 2008-03
Sub-type Article (original research)
DOI 10.1002/sim.3027
Volume 27
Issue 7
Start page 937
End page 953
Total pages 17
Place of publication West Sussex, United Kingdom
Publisher John Wiley & Sons
Language eng
Abstract In analysis of longitudinal data, the variance matrix of the parameter estimates is usually estimated by the ‘sandwich’ method, in which the variance for each subject is estimated by its residual products. We propose smooth bootstrap methods by perturbing the estimating functions to obtain ‘bootstrapped’ realizations of the parameter estimates for statistical inference. Our extensive simulation studies indicate that the variance estimators by our proposed methods can not only correct the bias of the sandwich estimator but also improve the confidence interval coverage. We applied the proposed method to a data set from a clinical trial of antibiotics for leprosy.
Keyword Bootstrap
Efficiency
Estimating functions
Longitudinal data
Resampling
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Mathematics and Physics
 
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Created: Wed, 17 Nov 2010, 13:55:34 EST