6533b825fe1ef96bd12830d5
RESEARCH PRODUCT
An Ordinal Joint Model for Breast Cancer
Hèctor PerpiñánHèctor PerpiñánCarmen ArmeroMontserrat RuéAnabel ForteCarles FornéMarisa BaréGuadalupe Gómezsubject
Oncologymedicine.medical_specialtyProportional hazards modelComputer scienceBayesian probabilityPosterior probabilityMarkov chain Monte CarloRandom effects modelmedicine.diseasesymbols.namesakeBreast cancerInternal medicineCovariateStatisticsmedicinesymbolsEvent (probability theory)description
We propose a Bayesian joint model to analyze the association between longitudinal measurements of an ordinal marker and time to a relevant event. The longitudinal process is defined in terms of a proportional-odds cumulative logit model and the time-to-event process through a left-truncated Cox proportional hazards model with information of the longitudinal marker and baseline covariates. Both longitudinal and survival processes are connected by a common vector of random effects.
year | journal | country | edition | language |
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2017-01-01 |