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Joint modelling compared with two stage methods for analysing longitudinal data and prospective outcomes: A simulation study of childhood growth and BP

Sayers, A.; Heron, J.; Smith, Andrew D. A. C.; Macdonald-Wallis, C.; Gilthorpe, M. S.; Steele, F.; Tilling, K.

Authors

A. Sayers

J. Heron

C. Macdonald-Wallis

M. S. Gilthorpe

F. Steele

K. Tilling



Abstract

© The Author(s) 2014. There is a growing debate with regards to the appropriate methods of analysis of growth trajectories and their association with prospective dependent outcomes. Using the example of childhood growth and adult BP, we conducted an extensive simulation study to explore four two-stage and two joint modelling methods, and compared their bias and coverage in estimation of the (unconditional) association between birth length and later BP, and the association between growth rate and later BP (conditional on birth length). We show that the two-stage method of using multilevel models to estimate growth parameters and relating these to outcome gives unbiased estimates of the conditional associations between growth and outcome. Using simulations, we demonstrate that the simple methods resulted in bias in the presence of measurement error, as did the two-stage multilevel method when looking at the total (unconditional) association of birth length with outcome. The two joint modelling methods gave unbiased results, but using the re-inflated residuals led to undercoverage of the confidence intervals. We conclude that either joint modelling or the simpler two-stage multilevel approach can be used to estimate conditional associations between growth and later outcomes, but that only joint modelling is unbiased with nominal coverage for unconditional associations.

Journal Article Type Article
Publication Date Feb 1, 2017
Journal Statistical Methods in Medical Research
Print ISSN 0962-2802
Electronic ISSN 1477-0334
Publisher SAGE Publications
Peer Reviewed Peer Reviewed
Volume 26
Issue 1
Pages 437-452
APA6 Citation Smith, A. D., Sayers, A., Heron, J., Smith, A. D. A. C., Macdonald-Wallis, C., Gilthorpe, M. S., …Tilling, K. (2017). Joint modelling compared with two stage methods for analysing longitudinal data and prospective outcomes: A simulation study of childhood growth and BP. Statistical Methods in Medical Research, 26(1), 437-452. https://doi.org/10.1177/0962280214548822
DOI https://doi.org/10.1177/0962280214548822
Keywords lifecourse epidemiology, joint model, multilevel model, measurement error, growth
Publisher URL http://dx.doi.org/10.1177/0962280214548822

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