INTRODUCTIONUnivariate shared random effect joint models for longitudinal and time‐to‐event data simultaneously model a longitudinal and a time‐to‐event outcome. The model consists of a longitudinal submodel and a time‐to‐event submodel linked through an association structure, which quantifies the relationship between the 2 outcomes. A range of options exist in the literature for each submodel (including linear mixed effects models or splines for the longitudinal submodel and proportional hazards or accelerated failure time models for the time‐to‐event submodels). Various association structures have been used, including sharing just random effects between the submodels, sharing the current longitudinal trajectory (both the fixed and random effects), or sharing the first derivative or slope of the longitudinal trajectory. This investigation focuses on joint models that concern a single continuous longitudinal and a single possibly censored time‐to‐event outcome, linked using an association structure consisting of shared zero mean random effects with one common association parameter, termed proportional association.Methods for the joint analysis of longitudinal and time‐to‐event data are commonly used in analyses to account for study dropout and measurement error in time varying covariates, whilst producing less biased estimates of study parameters. Powney et al discuss the Magnetic trial, which reported a longitudinal case with
Statistics in Medicine – Wiley
Published: Jan 15, 2018
Keywords: ; ; ; ;
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