Joint modeling of multivariate longitudinal data and survival data in several observational studies of Huntington's disease.
Jeffrey D LongJames A MillsPublished in: BMC medical research methodology (2018)
Joint modeling is an improvement over traditional survival modeling because it considers all the longitudinal observations of covariates that are predictive of an event. Predictions from joint models can have greater accuracy because they are tailored to account for individual variability. These predictions can provide relatively accurate characterizations of individual disease progression, which might be important in the timing of interventions, determining the qualification for appropriate clinical trials, and general genotypic analysis.