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Flexible Modelling of the Covariance Matrix in a Linear Random Effects Model
Author(s) -
Lesaffre Emmanuel,
Todem David,
Verbeke Geert,
Kenward Mike
Publication year - 2000
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/1521-4036(200011)42:7<807::aid-bimj807>3.0.co;2-3
Subject(s) - random effects model , generalized linear mixed model , covariance , mixed model , covariance matrix , longitudinal data , mathematics , linear model , parametric statistics , statistics , matrix (chemical analysis) , econometrics , computer science , medicine , data mining , meta analysis , materials science , composite material
A flexible approach is proposed for modelling the covariance matrix of a linear mixed model for longitudinal data. The method combines parametric modelling of the random effects part with flexible modelling of the serial correlation component. The approach is exemplified on weight gain data and on the evolution of height of children in their first year of life of the Jimma Infant Survival Study, an Ethiopian cohort study. The analyses show the usefulness of the approach.