Multilevel models for longitudinal data

Fiona Steele

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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.

JEL-codes: C1 (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (34)

Published in Journal of the Royal Statistical Society. Series A: Statistics in Society, 2008, 171(1), pp. 5-19. ISSN: 0964-1998

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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:52203

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