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Longitudinal Research with Latent Variables pp 37–96Cite as

Random Effects Models for Longitudinal Data

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Abstract

Mixed models have become very popular for the analysis of longitudinal data, partly because they are flexible and widely applicable, partly also because many commercially available software packages offer procedures to fit them. They assume that measurements from a single subject share a set of latent, unobserved, random effects which are used to generate an association structure between the repeated measurements. In this chapter, we give an overview of frequently used mixed models for continuous as well as discrete longitudinal data, with emphasis on model formulation and parameter interpretation. The fact that the latent structures generate associations implies that mixed models are also extremely convenient for the joint analysis of longitudinal data with other outcomes such as dropout time or some time-to-event outcome, or for the analysis of multiple longitudinally measured outcomes. All models will be extensively illustrated with the analysis of real data.

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Authors and Affiliations

  1. I-BioStat, Katholieke Universiteit Leuven, Leuven, Belgium

    Geert Verbeke

  2. I-BioStat, Universiteit Hasselt, Diepenbeek, Belgium

    Geert Molenberghs

  3. Department of Biostatistics, Erasmus University Medical Center, Rotterdam, The Netherlands

    Dimitris Rizopoulos

Authors
  1. Geert Verbeke
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  2. Geert Molenberghs
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  3. Dimitris Rizopoulos
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Correspondence to Geert Verbeke .

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Editors and Affiliations

  1. Dept. Econometrics & Operations, Research, Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam, 1081 HV, Netherlands

    Kees van Montfort

  2. Behavioural Science Institute, Radboud University Nijmegen, Montessorilaan 3, Nijmegen, 6525 HR, Netherlands

    Johan H.L. Oud

  3. , Department of Economics and Business, Universitat Pompeu Fabra, Ramon Trias Fargas 25-27, Barcelona, 08005, Spain

    Albert Satorra

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Verbeke, G., Molenberghs, G., Rizopoulos, D. (2010). Random Effects Models for Longitudinal Data. In: van Montfort, K., Oud, J., Satorra, A. (eds) Longitudinal Research with Latent Variables. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11760-2_2

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