Taking Account of Between-Patient Variability When Modeling Decline in Alzheimer's Disease - Joseph, L.; Wolfson, D. B.; Bélisle, P.; Brooks, J. O.; Mortimer, J. A.; Tinklenberg, J. R.; Yesavage, J. A. (American journal of epidemiology, 1999)
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. Am J Epidemiol 1999; 149:963–73.