Fitted JMbayes Object
An object returned by the jointModelBayes function, inheriting from class JMbayes and representing a fitted joint model for longitudinal and time-to-event data. Objects of this class have methods for the generic functions coef, confint, fixed.effects, logLik, plot, print, random.effects, summary, and vcov.
The following components must be included in a legitimate JMbayes object. - mcmc: a list with the MCMC samples for each parameter (except from the random effects if control argument keepRE is FALSE).
postMeans: a list with posterior means.
postModes: a list with posterior modes calculated using kernel desnisty estimation.
postVarsRE: a list with the posterior variance-covariance matrix for the random effects of each subject.
StErr: a list with posterior standard errors.
EffectiveSize: a list with effective sample sizes.
StDev: a list with posterior standard deviations.
CIs: a list with 95% credible intervals.
vcov: the variance-covariance matrix of the model's parameters based.
pD: the pD value.
DIC: the deviance information criterion value.
CPO: the conditional predictive ordinate value.
LPML: the log pseudo marginal likelihood value.
time: the time used to fit the model.
scales: a list with scaling constants in the Metropolis algorithm.
Covs: a list with the covariance matrices of the proposals in the Metropolis algorithm.
acceptRates: a list of acceptance rates.
x: a list with the design matrices for the longitudinal and event processes.
y: a list with the response vectors for the longitudinal and event processes.
Data: a list of data frames with the data used to fit the models.
Terms: a list of terms objects for the various parts of the joint model.
Funs: a list of functions used for the various parts of the joint model.
Forms: a list of formulas for the two submodels.
timeVar: the value of the timeVar argument
control: the value of the control argument.
densLongCheck: a logical indicating whether a scale parameter is required in the longitudinal submodel.
param: the value of the param argument.
priors: a list with the specification of the prior distributions for the model's parameters. This has the same components as the priors argument of the jointModelBayes function.
baseHaz: the value of the baseHaz argument.
df.RE: the value of the df.RE argument.
call: the matched call.
Dimitris Rizopoulos d.rizopoulos@erasmusmc.nl
jointModelBayes