Function reference • JMbayes2

All functions
`tvROC()` `tvAUC()` `calibration_plot()` `calibration_metrics()` `tvBrier()` `tvEPCE()` `create_folds()`	Time-Dependent Predictive Accuracy Measures for Joint Models
`aids` `aids.id`	Didanosine versus Zalcitabine in HIV Patients
`traceplot()` `ggtraceplot()` `gelman_diag()` `densplot()` `ggdensityplot()` `cumuplot()`	Various Methods for Functions from the coda Package
`crisk_setup()`	Transform Competing Risks Data in Long Format
`jm()` `value()` `coefs()` `slope()` `velocity()` `acceleration()` `area()` `vexpit()` `Dexpit()` `vexp()` `Dexp()` `vabs()` `vlog()` `vlog2()` `vlog10()` `vsqrt()` `poly2()` `poly3()` `poly4()` `tv()`	Joint Models for Longitudinal and Time-to-Event Data
`JMbayes2-package` `JMbayes2`	Extended Joint Models for Longitudinal and Time-to-Event Data
`coef()` `fixef()` `ranef()` `terms()` `model.frame()` `model.matrix()` `family()` `compare_jm()`	Various Methods for Standard Generics
`pbc2` `pbc2.id`	Mayo Clinic Primary Biliary Cirrhosis Data
`predict(<jm>)` `plot(<predict_jm>)` `predict(<jmList>)`	Predictions from Joint Models
`prothro` `prothros`	Prednisone versus Placebo in Liver Cirrhosis Patients
`rc_setup()`	Combine Recurring and Terminal Event Data in Long Format

Reference