Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts

We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models.

Source: Statistical Methods in Medical Research - October 1, 2016 Category: Statistics Authors: Howe, L. D., Tilling, K., Matijasevich, A., Petherick, E. S., Santos, A. C., Fairley, L., Wright, J., Santos, I. S., Barros, A. J., Martin, R. M., Kramer, M. S., Bogdanovich, N., Matush, L., Barros, H., Lawlor, D. A. Tags: Articles Source Type: research