Joint model for bivariate responses using left-truncated data in aging research

• Shengning Pan ^[1] ; Ardo Van den Hout
  1. [1] University College London

     University College London

     Reino Unido

     
• Localización: Proceedings of the 35th International Workshop on Statistical Modelling : July 20-24, 2020 Bilbao, Basque Country, Spain / Itziar Irigoien Garbizu (ed. lit.), Dae-Jin Lee (ed. lit.), Joaquín Martínez Minaya (ed. lit.), María Xosé Rodríguez Álvarez (ed. lit.), 2020, ISBN 978-84-1319-267-3, págs. 390-393
• Idioma: inglés
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  • Texto Completo Libro
• Resumen

  • In aging research, the change of cognitive function over time is of interest.We construct a bivariate shared random-e ects joint model to investigate it. Generally in a cognitive test, researchers use non-negative integers to re ect the level of cognitive function. We apply a bivariate binomial distribution in the joint model to investigate two test scores at the same. Moreover, to deal with the attrition, we use the Weibull hazard model and the Gompertz hazard model.

    The joint models are applied to the English Longitudinal Study of Ageing (ELSA) data.