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Multilevel models for longitudinal data

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  • Steele, Fiona

Abstract

Repeated measures and repeated events data have a hierarchical structure which can be analysed by using multilevel models. A growth curve model is an example of a multilevel random-coefficients model, whereas a discrete time event history model for recurrent events can be fitted as a multilevel logistic regression model. The paper describes extensions to the basic growth curve model to handle auto-correlated residuals, multiple-indicator latent variables and correlated growth processes, and event history models for correlated event processes. The multilevel approach to the analysis of repeated measures data is contrasted with structural equation modelling. The methods are illustrated in analyses of children's growth, changes in social and political attitudes, and the interrelationship between partnership transitions and childbearing.

Suggested Citation

  • Steele, Fiona, 2008. "Multilevel models for longitudinal data," LSE Research Online Documents on Economics 52203, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:52203
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    File URL: http://eprints.lse.ac.uk/52203/
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    References listed on IDEAS

    as
    1. Fiona Steele & Ian Diamond & Duolao Wang, 1996. "The determinants of the duration of contraceptive use in China: A multilevel multinomial discrete-hazards mdeling approach," Demography, Springer;Population Association of America (PAA), vol. 33(1), pages 12-23, February.
    2. Lee Lillard & Linda Waite, 1993. "A joint model of marital childbearing and marital disruption," Demography, Springer;Population Association of America (PAA), vol. 30(4), pages 653-681, November.
    3. Fiona Steele & Constantinos Kallis & Harvey Goldstein & Heather Joshi, 2005. "The relationship between childbearing and transitions from marriage and cohabitation in Britain," Demography, Springer;Population Association of America (PAA), vol. 42(4), pages 647-673, November.
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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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