Estimation for parameters of interest in random effects growth curve models

In this paper, we consider the general growth curve model with multivariate random effects covariance structure and provide a new simple estimator for the parameters of interest. This estimator is not only convenient for testing the hypothesis on the corresponding parameters, but also has higher eff...

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Bibliographic Details
Published in:Journal of multivariate analysis 2007-02, Vol.98 (2), p.317-327
Main Authors: Ip, Wai-Cheung, Wu, Mi-Xia, Wang, Song-Gui, Wong, Heung
Format: Article
Language:English
Subjects:
Best linear unbiased estimator
Exact sciences and technology
Exact test
Growth curve models
Growth curve models Random-effects Exact test Best linear unbiased estimator Maximum likelihood estimator
Growth models
Mathematics
Maximum likelihood estimator
Multivariate analysis
Parameter estimation
Parametric inference
Probability and statistics
Random-effects
Sciences and techniques of general use
Statistics
Studies
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Summary:In this paper, we consider the general growth curve model with multivariate random effects covariance structure and provide a new simple estimator for the parameters of interest. This estimator is not only convenient for testing the hypothesis on the corresponding parameters, but also has higher efficiency than the least-square estimator and the improved two-stage estimator obtained by Rao under certain conditions. Moreover, we obtain the necessary and sufficient condition for the new estimator to be identical to the best linear unbiased estimator. Examples of its application are given.
ISSN:0047-259X
1095-7243
DOI:10.1016/j.jmva.2006.04.001