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2010 Appropriate covariance-specification via penalties for penalized splines in mixed models for longitudinal data
Viani A.B. Djeundje, Iain D. Currie
Electron. J. Statist. 4: 1202-1224 (2010). DOI: 10.1214/10-EJS583

Abstract

A popular approach to smooth models for longitudinal data is to express the model as a mixed model, since this often leads to immediate model fitting with standard procedures. This approach is particularly appealing when truncated polynomials are used as a basis for the smoothing, as the mixed model representation is almost immediate. We show that this approach can lead to a severely biased estimate of the overall population effect and to confidence intervals with undesirable properties. We use penalization to investigate an alternative approach with either B-spline or truncated polynomial bases and show that this new approach does not suffer from the same defects. Our models are defined in terms of B-splines or truncated polynomials with appropriate penalties, but can be expressed as mixed models; this also gives access to fitting with standard procedures. We illustrate our methods with an analysis of two data sets: (a) a balanced data set on Canadian weather and (b) an unbalanced data set on the growth of children.

Citation

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Viani A.B. Djeundje. Iain D. Currie. "Appropriate covariance-specification via penalties for penalized splines in mixed models for longitudinal data." Electron. J. Statist. 4 1202 - 1224, 2010. https://doi.org/10.1214/10-EJS583

Information

Published: 2010
First available in Project Euclid: 8 November 2010

zbMATH: 1329.62198
MathSciNet: MR2735884
Digital Object Identifier: 10.1214/10-EJS583

Subjects:
Primary: 62G08
Secondary: 62J07

Rights: Copyright © 2010 The Institute of Mathematical Statistics and the Bernoulli Society

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