van den hout, A;
muniz, G;
(2016)
Joint models for discrete longitudinal outcomes in ageing research.
Journal of the Royal Statistical Society: Series C (Applied Statistics)
, 65
(1)
pp. 167-186.
10.1111/rssc.12114.
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Abstract
Given the aging population in the UK, statistical modelling of cognitive function in the older population is of interest. Joint models are formulated for survival and cognitive function in the older population. Because tests of cognitive function often result in discrete outcomes, binomial and beta–binomial mixed effects regression models are applied to analyse longitudinal measurements. Dropout due to death is accounted for by parametric survival models, where the choice of a Gompertz baseline hazard and the specification of the random-effects structure are of specific interest. The measurement model and the survival model are combined in a shared parameter joint model. Estimation is by marginal likelihood. The methods are used to analyse data from the Cambridge City over-75s cohort study and the English Longitudinal Study of Ageing
| Type: | Article |
|---|---|
| Title: | Joint models for discrete longitudinal outcomes in ageing research |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1111/rssc.12114 |
| Publisher version: | http://dx.doi.org/10.1111/rssc.12114 |
| Language: | English |
| Additional information: | This is the peer reviewed version of the following article: Journal of the Royal Statistical Society: Series C (Applied Statistics), which has been published in final form at http://dx.doi.org/10.1111/rssc.12114. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving http://olabout.wiley.com/WileyCDA/Section/id-820227.html#terms |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1468859 |
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