Document Detail

A nonlinear model with latent process for cognitive evolution using multivariate longitudinal data.
MedLine Citation:
PMID:  17156275     Owner:  NLM     Status:  MEDLINE    
Cognition is not directly measurable. It is assessed using psychometric tests, which can be viewed as quantitative measures of cognition with error. The aim of this article is to propose a model to describe the evolution in continuous time of unobserved cognition in the elderly and assess the impact of covariates directly on it. The latent cognitive process is defined using a linear mixed model including a Brownian motion and time-dependent covariates. The observed psychometric tests are considered as the results of parameterized nonlinear transformations of the latent cognitive process at discrete occasions. Estimation of the parameters contained both in the transformations and in the linear mixed model is achieved by maximizing the observed likelihood and graphical methods are performed to assess the goodness of fit of the model. The method is applied to data from PAQUID, a French prospective cohort study of ageing.
Cécile Proust; Hélène Jacqmin-Gadda; Jeremy M G Taylor; Julien Ganiayre; Daniel Commenges
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Biometrics     Volume:  62     ISSN:  0006-341X     ISO Abbreviation:  Biometrics     Publication Date:  2006 Dec 
Date Detail:
Created Date:  2006-12-12     Completed Date:  2007-03-07     Revised Date:  2013-06-06    
Medline Journal Info:
Nlm Unique ID:  0370625     Medline TA:  Biometrics     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1014-24     Citation Subset:  IM    
INSERM E0338, Université de Bordeaux 2, 146 rue Léo Saignat, 33076 Bordeaux Cedex, France.
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MeSH Terms
Aged, 80 and over
Aging / psychology*
Cohort Studies
Data Interpretation, Statistical
Likelihood Functions
Linear Models
Longitudinal Studies
Models, Psychological*
Multivariate Analysis
Nonlinear Dynamics*
Prospective Studies

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