A comparison of three random effects approaches to analyze repeated bounded outcome scores with an application in a stroke revalidation study

Marek Molas, Emmanuel Lesaffre

Research output: Contribution to journalArticleAcademicpeer-review

16 Citations (Scopus)


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. Copyright (C) 2008 John Wiley & Sons, Ltd.
Original languageUndefined/Unknown
Pages (from-to)6612-6633
Number of pages22
JournalStatistics in Medicine
Issue number30
Publication statusPublished - 2008

Research programs

  • EMC NIHES-01-66-01

Cite this