Title: Pairwise fitting of mixed models for the joint modeling of multivariate longitudinal profiles
Authors: Fieuws, Steffen ×
Verbeke, Geert #
Issue Date: Jun-2006
Series Title: Biometrics vol:62 issue:2 pages:424-431
Abstract: A mixed model is a flexible tool for joint modeling purposes, especially when the gathered data are unbalanced. However, computational problems due to the dimension of the joint covariance matrix of the random effects arise as soon as the number of outcomes and/or the number of used random effects per outcome increases. We propose a pairwise approach in which all possible bivariate models are fitted, and where inference follows from pseudo-likelihood arguments. The approach is applicable for linear, generalized linear, and nonlinear mixed models, or for combinations of these. The methodology will be illustrated for linear mixed models in the analysis of 22-dimensional, highly unbalanced, longitudinal profiles of hearing thresholds.
ISSN: 0006-341X
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat)
× corresponding author
# (joint) last author

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