Title
Flexible estimation of serial correlation in nonlinear mixed models Flexible estimation of serial correlation in nonlinear mixed models
Author
Faculty/Department
Faculty of Sciences. Mathematics and Computer Science
Faculty of Pharmaceutical, Biomedical and Veterinary Sciences . Biomedical Sciences
Publication type
article
Publication
Abingdon ,
Subject
Mathematics
Human medicine
Source (journal)
Journal of applied statistics. - Abingdon
Volume/pages
37(2010) :5 , p. 833-846
ISSN
0266-4763
ISI
000277584100010
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
In the conventional linear mixed-effects model, four structures can be distinguished: fixed effects, random effects, measurement error and serial correlation. The latter captures the phenomenon that the correlation structure within a subject depends on the time lag between two measurements. While the general linear mixed model is rather flexible, the need has arisen to further increase flexibility. In addition to work done in the area, we propose the use of spline-based modeling of the serial correlation function, so as to allow for additional flexibility. This approach is applied to data from a pre-clinical experiment in dementia which studied the eating and drinking behavior in mice.
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