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Multilevel multivariate modelling of childhood growth, numbers of growth measurements and adult characteristics

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  • Harvey Goldstein
  • Daphne Kounali

Abstract

Summary. A general latent normal model for multilevel data with mixtures of response types is extended in the case of ordered responses to deal with variates having a large number of categories and including count data. An example is analysed by using repeated measures data on child growth and adult measures of body mass index and glucose. Applications are described that are concerned with the flexible prediction of adult measurements from collections of growth measurements and for studying the relationship between the number of measurement occasions and growth trajectories.

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  • Harvey Goldstein & Daphne Kounali, 2009. "Multilevel multivariate modelling of childhood growth, numbers of growth measurements and adult characteristics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(3), pages 599-613, June.
    • Handle: RePEc:bla:jorssa:v:172:y:2009:i:3:p:599-613
    DOI: 10.1111/j.1467-985X.2008.00576.x
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    Cited by:

    1. Steele, Fiona & Clarke, Paul & Leckie, George & Allan, Julia & Johnston, Derek, 2017. "Multilevel structural equation models for longitudinal data where predictors are measured more frequently than outcomes: an application to the effects of stress on the cognitive function of nurses," LSE Research Online Documents on Economics 64893, London School of Economics and Political Science, LSE Library.
    2. Fiona Steele & Paul Clarke & George Leckie & Julia Allan & Derek Johnston, 2017. "Multilevel structural equation models for longitudinal data where predictors are measured more frequently than outcomes: an application to the effects of stress on the cognitive function of nurses," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(1), pages 263-283, January.
    3. Shin Yongyun & Raudenbush Stephen W., 2013. "Efficient Analysis of Q-Level Nested Hierarchical General Linear Models Given Ignorable Missing Data," The International Journal of Biostatistics, De Gruyter, vol. 9(1), pages 1-25, September.
    4. Yuda Zhu & Robert E. Weiss, 2013. "Modeling Seroadaptation and Sexual Behavior Among HIV-super-+ Study Participants with a Simultaneously Multilevel and Multivariate Longitudinal Count Model," Biometrics, The International Biometric Society, vol. 69(1), pages 214-224, March.
    5. Francesco Lagona & Antonello Maruotti & Fabio Padovano, 2015. "Multilevel multivariate modelling of legislative count data, with a hidden Markov chain," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(3), pages 705-723, June.

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