JMbayesObject: Fitted JMbayes Object

In JMbayes: Joint Modeling of Longitudinal and Time-to-Event Data under a Bayesian Approach

Description

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.

Value

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.

Author(s)

Dimitris Rizopoulos [e-mail]

See Also

jointModelBayes

JMbayes documentation built on Jan. 9, 2020, 9:07 a.m.