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

Ardo van den Hout, Graciela Muniz-Terrera and Fiona E. Matthews

Computational Statistics & Data Analysis, 2013, vol. 57, issue 1, 684-698

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.

Keywords: Beta-binomial distribution; Latent class model; Mini-mental state examination; Random-effects model (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:57:y:2013:i:1:p:684-698

DOI: 10.1016/j.csda.2012.07.024

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