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Change point models for cognitive tests using semi-parametric maximum likelihood

Van Den Hout, Ardo; Muniz-Terrera, Graciela; Matthews, Fiona E.

Authors

Ardo Van Den Hout

Graciela Muniz-Terrera



Abstract

Random-effects change point models are formulated for longitudinal data obtained from cognitive tests. The conditional distribution of the response variable in a change point model is often assumed to be normal even if the response variable is discrete and shows ceiling effects. For the sum score of a cognitive test, the binomial and the beta-binomial distributions are presented as alternatives to the normal distribution. Smooth shapes for the change point models are imposed. Estimation is by marginal maximum likelihood where a parametric population distribution for the random change point is combined with a non-parametric mixing distribution for other random effects. An extension to latent class modelling is possible in case some individuals do not experience a change in cognitive ability. The approach is illustrated using data from a longitudinal study of Swedish octogenarians and nonagenarians that began in 1991. Change point models are applied to investigate cognitive change in the years before death. © 2012 Elsevier B.V. All rights reserved.

Citation

Van Den Hout, A., Muniz-Terrera, G., & Matthews, F. E. (2013). Change point models for cognitive tests using semi-parametric maximum likelihood. Computational Statistics and Data Analysis, 57(1), 684-698. https://doi.org/10.1016/j.csda.2012.07.024

Journal Article Type Article
Publication Date Jan 1, 2013
Deposit Date Dec 8, 2023
Journal Computational Statistics and Data Analysis
Print ISSN 0167-9473
Publisher Elsevier
Volume 57
Issue 1
Pages 684-698
DOI https://doi.org/10.1016/j.csda.2012.07.024
Public URL https://hull-repository.worktribe.com/output/4454688