Title: High dimensional multivariate mixed models for binary questionnaire data
Authors: Fieuws, Steffen ×
Verbeke, Geert
Boen, Filip
Delecluse, Christophe #
Issue Date: 2006
Publisher: The Society
Series Title: Journal of the Royal Statistical Society C, Applied Statistics vol:55 issue:part 4 pages:449-460
Abstract: Questionnaires that are used to measure the effect of an intervention often consist of different sets of items, each set possibly measuring another concept. Mixed models with set-specific random effects are a flexible tool to model the different sets of items jointly. However, computational problems typically arise as the number of sets increases. This is especially true when the random-effects distribution cannot be integrated out analytically, as with mixed models for binary data. A pairwise modelling strategy, in which all possible bivariate mixed models are fitted and where inference follows from pseudolikelihood theory, has been proposed as a solution. This approach has been applied to assess the effect of physical activity on psychocognitive functioning, the latter measured by a battery of questionnaires.
ISSN: 0035-9254
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat)
Research Centre for Exercise & Sport Psychology, and Coaching (-)
Exercise Physiology Research Group
Policy in Sports & Physical Activity Research Group
× corresponding author
# (joint) last author

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