Galán-Arcicollar, Cristina; Najera-Zuloaga, Josu; Lee, Dae-Jin Patient-reported outcomes and survival analysis of chronic obstructive pulmonary disease patients: a two-stage joint modelling approach. (English) Zbl 1548.62324 SORT 48, No. 2, 155-182 (2024). Summary: Joint modelling has gained attention in longitudinal studies incorporating biomarkers and survival data. In the context of chronic diseases, patient evolution is often tracked through multiple assessments, with patient-reported outcomes playing a crucial role. The Beta-Binomial distribution is suggested as a suitable model for these longitudinal variables. However, its integration into joint modelling remains unexplored. This study introduces an estimation procedure for analyzing longitudinal patient-reported outcomes and survival data together. We compare different estimation approaches through simulation experiments, including the proposed model. Furthermore, the methodologies are applied to real data from a follow-up study on chronic obstructive pulmonary disease patients. MSC: 62P10 Applications of statistics to biology and medical sciences; meta analysis 62N02 Estimation in survival analysis and censored data 62N03 Testing in survival analysis and censored data Keywords:joint modelling; beta-binomial regression; patient-reported outcomes; survival analysis Software:nlme; JM; PROreg × Cite Format Result Cite Review PDF Full Text: DOI References: [1] Alvares, D. and Leiva-Yamaguchi, V. (2023). A two-stage approach for Bayesian joint models: reducing complexity while maintaining accuracy. Statistics and Computing, 33(5):1-11. ISSN: 15731375. DOI: 10.1007/s11222-023-10281-9. URL: https://doi.org/10.1007/s11222-023-10281-9. · Zbl 1517.62003 · doi:10.1007/s11222-023-10281-9 [2] Arisido, M. W., Antolini, L., Bernasconi, D. P., Valsecchi, M. G. and Rebora, P. (2019). 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