Bayesian joint modeling of ordinal longitudinal measurements and competing risks survival data for analysing Tehran Lipid and Glucose Study.

Journal of Biopharmaceutical Statistics
T BaghfalakiBagher Pahlavanzadeh

Abstract

In this paper, joint modeling of longitudinal ordinal measurements and time to some events of interest as competing risks is discussed. For this purpose, a latent variable sub-model under linear mixed-effects assumption is considered for modeling ordinal longitudinal measurements. Also, a Weibull cause-specific sub-model is used to model competing risks data. These two sub-models are simultaneously considered in a unique model by a shared parameter model framework. Some simulation studies are performed for illustration of the proposed approaches; also, the proposed approaches are used for analyzing 15 years of lipid and glucose follow-up study in Tehran.

References

Aug 21, 2003·Biometrics·Elizabeth R Brown, Joseph G Ibrahim
Aug 23, 2003·Biostatistics·R HendersonA Dobson
Feb 5, 2008·International Journal of Cardiology·M TohidiF Azizi
Mar 29, 2014·Statistics in Medicine·Eleni-Rosalina AndrinopoulouEmmanuel Lesaffre
Apr 5, 2014·Journal of Biopharmaceutical Statistics·T BaghfalakiR Hashemi

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Citations

Apr 28, 2021·Journal of Biopharmaceutical Statistics·P MehdizadehM Ganjali

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Software Mentioned

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