The pattern of deterioration in patients with Alzheimer's disease is highly variable within a given population.
With recent speculation that the apolipoprotein E allele may influence rate of decline and claims that certain drugs may slow the course of the disease, there is a compelling need for sound statistical methodology to address these questions.
Current statistical methods for describing decline do not adequately take into account between-patient variability and possible floor and/or ceiling effects in the scale measuring decline, and they fail to allow for uncertainty in disease onset.
In this paper, the authors analyze longitudinal Mini-Mental State Examination scores from two groups of Alzheimer's disease subjects from Palo Alto, California, and Minneapolis, Minnesota, in 1981-1993 and 1986-1988, respectively.
A Bayesian hierarchical model is introduced as an elegant means of simultaneously overcoming all of the difficulties referred to above.
Mots-clés Pascal : Démence Alzheimer, Epidémiologie, Méthodologie, Modèle statistique, Homme, Etats Unis, Amérique du Nord, Amérique, Système nerveux pathologie, Système nerveux central pathologie, Encéphale pathologie, Maladie dégénérative
Mots-clés Pascal anglais : Alzheimer disease, Epidemiology, Methodology, Statistical model, Human, United States, North America, America, Nervous system diseases, Central nervous system disease, Cerebral disorder, Degenerative disease
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 99-0300615
Code Inist : 002B30A01A1. Création : 16/11/1999.