Joint Modeling of Longitudinal and Time-to-Event Data under a Bayesian Approach
Anova Method for Fitted Joint Models
Time-Dependent ROCs and AUCs for Joint Models
Combines Predictions for Bayesian Model Averaging
Estimated Coefficients and Confidence Intervals for Joint Models
Dynamic Information
Derivatives and Integrals of B-splines and Natural Cubic splines
A Dynamic Discrimination Index for Joint Models
Dynamic Information of an Extra Longitudinal Measurement
Fitted Values and Residuals for Joint Models
The Generalized Student's t Distribution
Individualized Predictions from Linear Mixed Models
Joint Modeling of Longitudinal and Time-to-Event Data in R under a Bay...
Fitted JMbayes Object
Joint Models for Longitudinal and Time-to-Event Data
Log-Likelihood for Joint Models
Calculates Marginal Subject-specific Log-Likelihood Contributions
Multivariate Mixed Models
Multivariate Joint Models for Longitudinal and Time-to-Event Data
Mayo Clinic Primary Biliary Cirrhosis Data
Plot Method for survfit.JMbayes and survfit.mvJMbayes Objects
MCMC Diagnostics for Joint Models
Prediction Errors for Joint Models
Predictions for Joint Models
Random Effects Estimates for Joint Models
Shiny Application for Dynamic Predictions
Prediction in Joint Models
Time-Varying Effects using P-splines
xtable Method from Joint Models.
Shared parameter models for the joint modeling of longitudinal and time-to-event data using MCMC; Dimitris Rizopoulos (2016) <doi:10.18637/jss.v072.i07>.