A random change point model for assessing variability in repeated measures of cognitive function.
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.
Dominicus
Annica
A
Biostatistics, AstraZeneca R&D, SE-151 85 Södertälje, Sweden. Annica.Dominicus@astrazeneca.com
Ripatti
Samuli
S
Pedersen
Nancy L
NL
Palmgren
Juni
J
D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D000704:Analysis of Variance; D001499:Bayes Theorem; D003071:Cognition / Q000502:physiology*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005260:Female; D005500:Follow-Up Studies; D005838:Genotype; D006801:Humans; D008297:Male; D008390:Markov Chains; D008875:Middle Aged; D015233:Models, Statistical; D009010:Monte Carlo Method; D009483:Neuropsychological Tests; D012737:Sex Factors; D011795:Surveys and Questionnaires; D013997:Time Factors; D014427:Twins