Department of Psychology, University of Leuven, Universit of Leuven, Belgium.
Br J Math Stat Psychol. 2011 Feb;64(Pt 1):134-60. doi: 10.1348/000711010X498621.
We focus on comparing different modelling approaches for intensive longitudinal designs. Two methods are scrutinized, namely the widely used linear mixed model (LMM) and the relatively unexplored Ornstein-Uhlenbeck (OU) process based state-space model. On the one hand, we show that given certain conditions they result in equivalent outcomes. On the other hand, we consider it important to emphasize that their perspectives are different and that one framework might better address certain types of research questions than the other. We show that, compared to a LMM, an OU process based approach can cope with modelling inter-individual differences in aspects that are more substantively interesting. However, the estimation of the LMM is faster and the model is more straightforward to implement. The models are illustrated through an experience sampling study.
我们专注于比较密集纵向设计的不同建模方法。本文研究了两种方法，即广泛使用的线性混合模型（LMM）和相对未探索的基于 Ornstein-Uhlenbeck（OU）过程的状态空间模型。一方面，我们表明在某些条件下，它们会产生等效的结果。另一方面，我们认为强调它们的观点不同，并且一个框架可能比另一个框架更能解决某些类型的研究问题是很重要的。我们表明，与 LMM 相比，基于 OU 过程的方法可以更好地处理个体间差异方面更具实质性意义的问题。然而，LMM 的估计速度更快，模型更容易实现。通过经验抽样研究来说明这些模型。
