INLAjoint.object {INLAjoint}

Fitted joint object

Description

An object of class INLAjoint returned by the joint function that fits a joint model to multivariate longitudinal and time-to-event data. The following functions can apply to objects of this class: plot, print, summary and priors.used.

Usage

INLAjoint.object

Format

An object of class NULL of length 0.

Value

A list with the following components:

names.fixed

a vector with the name of the fixed effects of the model. The corresponding submodel is indicated by the suffix including a letter and a number ("L" for longitudinal and "S" for survival).

summary.fixed

summary statistics for the fixed effects of the model. The summary statistics sorted by longitudinal and survival components are available by applying the summary function to the INLAjoint object.

summary.fixed

marginals for the fixed effects of the model.

mlik

log marginal-likelihood.

cpo

Conditional Predictive Ordinate.

gcpo

Group-Conditional Predictive Ordinate.

po

Predictive ordinate.

waic

Widely applicable Bayesian information criterion

model.random

a vector with the name of the random parameters of the model, possibly including the following components:

RW1 model and RW2 model

Random walk of order 1 or 2 corresponding to Bayesian smoothing splines for the baseline hazard risk

IID model

Univariate random effect.

IIDKD model

Multivariate random effects.

Copy

association parameter.

summary.random

summary statistics for the random parameters of the model.

marginals.random

marginals for the random parameters of the model.

size.random

size of the random parameters of the model.

summary.linear.predictor

summary statistics of the linear predictors.

marginals.linear.predictor

marginals for the linear predictors.

summary.fitted.values

summary statistics of the fitted values.

marginals.fitted.values

marginals for the fitted values.

size.linear.predictor

size of the linear predictors.

summary.hyperpar

summary statistics for the hyperparameters of the model. The summary statistics sorted by longitudinal and survival components are available by applying the summary function to the INLAjoint object. Particularly, this is the raw output of INLA and therefore the precision of the residual errors and baseline hazard functions hyperparameters are provided. Similarly, the Cholesky matrix is given for the random-effects. The summary function can easily return either variance and covariance or standard deviations and correlations for all these hyperparameters.

marginals.hyperpar

marginals for the hyperparameters of the model.

internal.summary.hyperpar

summary of the internal hyperparameters, this is similar to the summary of the hyperparameters but here they are provided as used for the computations (logarithm scale for residual error and baseline risk hyperparameters).

internal.marginals.hyperpar

marginals for the internal hyperparameters of the model.

misc

miscellaneous (as provided in the INLA output).

dic

Deviance Information Criterion.

mode

.

joint.hyper

.

nhyper

.

version

Version of INLA.

cpu.used

Computation time of INLA.

all.hyper

.

.args

.

call

INLA call.

selection

information about parameters for sampling with inla.rjmarginal.

cureVar

informations about cure fraction submodel for mixture cure survival models.

variant

information about variant for Weibull baseline hazards.

SurvInfo

some information about survival submodels (names of event indicator and event time variables as well as baseline hazard).

famLongi

list of distributions for the longitudinal markers.

corLong

boolean indicating if random effects are correlated accross markers.

control.link

informations about link function (1=default).

longOutcome

name of longitudinal outcomes.

survOutcome

name of survival outcomes.

assoc

vector with names of all association parameters (longi-surv).

id

name of the id variable.

timeVar

name of time variable.

range

information about range of X-axis values for non-linear associations.

REstruc

names of the grouped random effects for the longitudinal markers.

mat_k

contains the list of random effects covariance matrices when they are fixed as they are not part of the estimated parameters (used for displaying them in summary).

fixRE

list of the size of number of groups of random effects, each element is a boolean indicating if the random effects of the group is fixed (TRUE) or estimated (FALSE).

lonFacChar

list of factors and character covariates included in the longitudinal submodels to keep track of modalities (used internally when doing predictions to reconstruct categorical covariates).

survFacChar

same as lonFacChar but for survival submodels.

corRE

list indicating if groups of random effects are correlated within longitudinal submodels.

basRisk

list of the baseline risk used for each survival submodel.

priors_used

informations about priors used in the model, internally used to display priors in plots (with argument priors=TRUE in the call of the plot function). Note that priors can also be displayed with the function priors.used() applied to an INLAjoint object.

dataLong

name of the longitudinal dataset.

dataSurv

name of the survival dataset.

See Also

joint.