10. Modelling Longitudinal Data

  1. Peter M. Fayers1,2 and
  2. David Machin3,4

Published Online: 8 MAR 2002

DOI: 10.1002/0470846283.ch10

Quality of Life: Assessment, Analysis and Interpretation

Quality of Life: Assessment, Analysis and Interpretation

How to Cite

Fayers, P. M. and Machin, D. (2000) Modelling Longitudinal Data, in Quality of Life: Assessment, Analysis and Interpretation, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/0470846283.ch10

Author Information

  1. 1

    Medical Research Council Clinical Trials Unit, London, UK

  2. 2

    Unit of Applied Clinical Research, Norwegian University of Science and Technology, Trondheim, Norway

  3. 3

    NMRC Clinical Trials & Epidemiology Research Unit, Singapore

  4. 4

    School of Health and Related Research, University of Sheffield, UK

Publication History

  1. Published Online: 8 MAR 2002
  2. Published Print: 18 APR 2000

ISBN Information

Print ISBN: 9780471968610

Online ISBN: 9780470846285



  • auto-correlation;
  • repeated measures;
  • ANOVA;
  • auto-regression;
  • generalised estimating equations;
  • covariates;
  • logistic models;


This chapter describes a modelling approach to the description of longitudinal data, which permits both estimation of effect sizes and statistical tests of hypotheses. These models take account of the fact that successive QoL assessments by a particular patient are likely to be correlated. The alternative approaches are classified as repeated measures, general estimating equations and multi-level models. They all require the specification of an auto-correlation structure and this is described.