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.

译文

:离散有界结果分数(BOS),即在有限的时间间隔内进行的离散测量,通常在实践中会出现。示例包括合规性措施,生活质量措施等。在本文中,我们研究了三种相关的随机效应方法,以BOS作为响应来分析纵向研究:(1)将线性混合效应(LM)模型应用于经逻辑转换的改良BOS ; (2)假设离散BOS是潜在随机变量的粗化版本的模型,在对数正态变换之后,该模型满足LM模型; (3)随机效应概率模型。我们还考虑了扩展,即BOS的可变性取决于协变量。通过模拟研究和一个纵向项目对这些方法进行了对比,该项目记录了四个欧洲国家中运动恢复和功能恢复的卒中康复情况。

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