The linear mixed model and the hierarchical Ornstein-Uhlenbeck model: Some equivalences and differences

Zita Oravecz, Francis Tuerlinckx

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Pages (from-to)134-160
Number of pages27
JournalBritish Journal of Mathematical and Statistical Psychology
Volume64
Issue number1
DOIs
StatePublished - Feb 1 2011

Fingerprint

Linear Mixed Model
Linear Models
Ornstein-Uhlenbeck Process
Equivalence
Space Simulation
Sampling Studies
Individual Differences
State-space Model
Modeling
Individuality
Model
Research

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Arts and Humanities (miscellaneous)
  • Psychology(all)

Cite this

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The linear mixed model and the hierarchical Ornstein-Uhlenbeck model : Some equivalences and differences. / Oravecz, Zita; Tuerlinckx, Francis.

In: British Journal of Mathematical and Statistical Psychology, Vol. 64, No. 1, 01.02.2011, p. 134-160.

Research output: Contribution to journalArticle

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