Joint Models of Survival and Multivariate Longitudinal Data
Anova for joint models
Bootstrapping a joint object
Obtain conditional distribution of the random effects
Dynamic predictions for survival sub-model in a multivariate joint mod...
Extract AIC from a joint model fit.
Obtain joint model fitted values
Extract fixed effects from a joint object.
tools:::Rd_package_title("gmvjoint")
Fitted joint object
Fit a joint model to time-to-event and multivariate longitudinal data
Log-likelihood for joint model.
Parsing the survival formula and constructing all survival-related dat...
Plot posterior distribution of the random effects for a joint model.
Plot conditional survival probabilities.
Plot joint model residuals
Plot receiver operator characteristics.
Extract random effects from a joint object.
Obtain joint model residuals
Simulate realisations from a generalised poisson distribution
Receiver Operator Characteristics (ROC) for a joint model.
Simulate data from a multivariate joint model
Summary of an joint object.
Extract the variance-covariance matrix from a joint fit.
Print an LaTeX-ready xtable for a joint object.
Fit joint models of survival and multivariate longitudinal data. The longitudinal data is specified by generalised linear mixed models. The joint models are fit via maximum likelihood using an approximate expectation maximisation algorithm. Bernhardt (2015) <doi:10.1016/j.csda.2014.11.011>.
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