Smooth bootstrap methods for analysis of longitudinal data

Li, Yue & Wang, You-Gan (2008) Smooth bootstrap methods for analysis of longitudinal data. Statistics in Medicine, 27(7), pp. 937-953.

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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.

Impact and interest:

4 citations in Scopus
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3 citations in Web of Science®

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ID Code: 90457
Item Type: Journal Article
Refereed: Yes
Keywords: bootstrap, efficiency, estimating functions, longitudinal data, resampling, smooth bootstrap, generalized estimating equations, linear-models, regression, variance, misspecification, estimator
DOI: 10.1002/sim.3027
ISSN: 0277-6715
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 17 Nov 2015 03:03
Last Modified: 17 Nov 2015 03:03

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