UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Bivariate joint models for survival and change of cognitive function

Van Den Hout, Arie; Pan, Shengning; (2023) Bivariate joint models for survival and change of cognitive function. Statistical Methods in Medical Research , 32 (3) pp. 474-492. 10.1177/096228022211463. Green open access

[thumbnail of Van Den Hout_09622802221146307.pdf]
Preview
Text
Van Den Hout_09622802221146307.pdf

Download (1MB) | Preview

Abstract

Changes in cognitive function over time are of interest in ageing research. A joint model is constructed to investigate. Generally, cognitive function is measured through more than one test, and the test scores are integers. The aim is to investigate two test scores and use an extension of a bivariate binomial distribution to define a new joint model. This bivariate distribution model the correlation between the two test scores. To deal with attrition due to death, the Weibull hazard model and the Gompertz hazard model are used. A shared random-effects model is constructed, and the random effects are assumed to follow a bivariate normal distribution. It is shown how to incorporate random effects that link the bivariate longitudinal model and the survival model. The joint model is applied to the English Longitudinal Study of Ageing data.

Type: Article
Title: Bivariate joint models for survival and change of cognitive function
Open access status: An open access version is available from UCL Discovery
DOI: 10.1177/096228022211463
Publisher version: https://doi.org/10.1177/096228022211463
Language: English
Additional information: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page
Keywords: Joint model, bivariate binomial distribution, cognitive function, survival analysis, shared random-effects model
UCL classification: UCL
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/10161985
Downloads since deposit
38Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item