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A random change point model for assessing variability in repeated measures of cognitive function
Author(s) -
Dominicus Annica,
Ripatti Samuli,
Pedersen Nancy L.,
Palmgren Juni
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3380
Subject(s) - random effects model , variance (accounting) , markov chain monte carlo , gibbs sampling , cognition , statistics , point process , econometrics , markov chain , function (biology) , mathematics , computer science , monte carlo method , psychology , bayesian probability , medicine , meta analysis , accounting , neuroscience , evolutionary biology , business , biology
Some cognitive functions undergo transitions in old age, which motivates the use of a change point model for the individual trajectory. The age when the change occurs varies between individuals and is treated as random. We illustrate the properties of a random change point model and use it for data from a Swedish study of change in cognitive function in old age. Variance estimates are obtained from Markov chain Monte Carlo simulation using Gibbs sampling. The random change point model is compared with models within the family of linear random effects models. The focus is on the ability to capture variability in measures of cognitive function. The models make different assumptions about the variance over the age span, and we demonstrate that the random change point model has the most reasonable structure. Copyright © 2008 John Wiley & Sons, Ltd.