Estimation of bivariate measurements having different change points, with application to cognitive ageing

Longitudinal studies of ageing make repeated observations of multiple measurements on each subject. Change point models are often used to model longitudinal data. We demonstrate the use of Bayesian and profile likelihood methods to simultaneously estimate different change points in the longitudinal...

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Published inStatistics in medicine Vol. 20; no. 24; pp. 3695 - 3714
Main Authors Hall, Charles B., Ying, Jun, Kuo, Lynn, Sliwinski, Martin, Buschke, Herman, Katz, Mindy, Lipton, Richard B.
Format Journal Article Conference Proceeding
LanguageEnglish
Published Chichester, UK John Wiley & Sons, Ltd 30.12.2001
Wiley
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Summary:Longitudinal studies of ageing make repeated observations of multiple measurements on each subject. Change point models are often used to model longitudinal data. We demonstrate the use of Bayesian and profile likelihood methods to simultaneously estimate different change points in the longitudinal course of two different measurements of cognitive function in subjects in the Bronx Aging Study who developed Alzheimer's disease (AD). Analyses show that accelerated memory decline, as measured by Buschke Selective Reminding, begins between seven and eight years before diagnosis of AD, while decline in performance on speeded tasks as measured by WAIS Performance IQ begins slightly more than two years before diagnosis, significantly after the decline in memory. Copyright © 2001 John Wiley & Sons, Ltd.
Bibliography:ark:/67375/WNG-RN4HHMSL-J
National Institute on Aging - No. AG-03949; No. AG-13631
istex:1D56B33DE71F77D0AFB4E31CA8F60BD0C3ECDE2F
Presented at the International Society for Clinical Biostatistics Twenty-first International Meeting, Trento, Italy, September 2000.
ArticleID:SIM1113
Presented at the International Society for Clinical Biostatistics Twenty‐first International Meeting, Trento, Italy, September 2000.
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0277-6715
1097-0258
DOI:10.1002/sim.1113