The rstanarm model-fitting functions return an object of class
'stanreg', which is a list containing at a minimum the components listed
below. Each stanreg object will also have additional classes (e.g. 'aov',
'betareg', 'glm', 'polr', etc.) and several additional components depending
on the model and estimation algorithm.
Some additional details apply to models estimated using the stan_mvmer
or stan_jm modelling functions. The stan_mvmer modelling
function returns an object of class 'stanmvreg', which inherits the
'stanreg' class, but has a number of additional elements described in the
subsection below. The stan_jm modelling function returns an object of class
'stanjm', which inherits both the 'stanmvreg' and 'stanreg'
classes, but has a number of additional elements described in the subsection below.
Both the 'stanjm' and 'stanmvreg' classes have several of their own
methods for situations in which the default 'stanreg' methods are not
suitable; see the See Also section below.
coefficientsPoint estimates, as described in print.stanreg.
sesStandard errors based on mad, as described in
print.stanreg.
residualsResiduals of type 'response'.
fitted.valuesFitted mean values. For GLMs the linear predictors are transformed by the inverse link function.
linear.predictorsLinear fit on the link scale. For linear models this is the same as
fitted.values.
covmatVariance-covariance matrix for the coefficients based on draws from the posterior distribution, the variational approximation, or the asymptotic sampling distribution, depending on the estimation algorithm.
model,x,yIf requested, the the model frame, model matrix and response variable used, respectively.
familyThe family object used.
callThe matched call.
formulaThe model formula.
data,offset,weightsThe data, offset, and weights arguments.
algorithmThe estimation method used.
prior.infoA list with information about the prior distributions used.
stanfit,stan_summaryThe object of stanfit-class returned by RStan and a
matrix of various summary statistics from the stanfit object.
rstan_versionThe version of the rstan package that was used to fit the model.
cnmsThe names of the grouping factors and group specific parameters, collapsed across the longitudinal or glmer submodels.
flevelsThe unique factor levels for each grouping factor, collapsed across the longitudinal or glmer submodels.
n_markersThe number of longitudinal or glmer submodels.
n_yobsThe number of observations for each longitudinal or glmer submodel.
n_grpsThe number of levels for each grouping factor (for models estimated using
stan_jm, this will be equal to n_subjects if the
individual is the only grouping factor).
runtimeThe time taken to fit the model (in minutes).
id_var,time_varThe names of the variables distinguishing between individuals, and representing time in the longitudinal submodel.
n_subjectsThe number of individuals.
n_eventsThe number of non-censored events.
eventtime,statusThe event (or censoring) time and status indicator for each individual.
basehazA list containing information about the baseline hazard.
assocAn array containing information about the association structure.
epsilonThe width of the one-sided difference used to numerically evaluate the slope of the longitudinal trajectory; only relevant if a slope-based association structure was specified (e.g. etaslope, muslope, etc).
qnodesThe number of Gauss-Kronrod quadrature nodes used to evaluate the cumulative hazard in the joint likelihood function.
stanreg-methods, stanmvreg-methods