A comparison of three random effects approaches to analyze repeated bounded outcome scores with an application in a stroke revalidation study.
Discrete bounded outcome scores (BOS), i.e. discrete measurements that are restricted on a finite interval, often occur in practice. Examples are compliance measures, quality of life measures, etc. In this paper we examine three related random effects approaches to analyze longitudinal studies with a BOS as response: (1) a linear mixed effects (LM) model applied to a logistic transformed modified BOS; (2) a model assuming that the discrete BOS is a coarsened version of a latent random variable, which after a logistic-normal transformation, satisfies an LM model; and (3) a random effects probit model. We consider also the extension whereby the variability of the BOS is allowed to depend on covariates. The methods are contrasted using a simulation study and on a longitudinal project, which documents stroke rehabilitation in four European countries using measures of motor and functional recovery.
Molas
Marek
M
Department of Biostatistics, Erasmus Medical Center, Rotterdam, The Netherlands.
Lesaffre
Emmanuel
E
D003198:Computer Simulation; D005060:Europe; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D008137:Longitudinal Studies; D015337:Multicenter Studies as Topic; D018401:Sample Size; D000071939:Stroke Rehabilitation