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.
coefficients
Point estimates, as described in print.stanreg
.
ses
Standard errors based on mad
, as described in
print.stanreg
.
residuals
Residuals of type 'response'
.
fitted.values
Fitted mean values. For GLMs the linear predictors are transformed by the inverse link function.
linear.predictors
Linear fit on the link scale. For linear models this is the same as
fitted.values
.
covmat
Variance-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,y
If requested, the the model frame, model matrix and response variable used, respectively.
family
The family
object used.
call
The matched call.
formula
The model formula
.
data,offset,weights
The data
, offset
, and weights
arguments.
algorithm
The estimation method used.
prior.info
A list with information about the prior distributions used.
stanfit,stan_summary
The object of stanfit-class
returned by RStan and a
matrix of various summary statistics from the stanfit object.
rstan_version
The version of the rstan package that was used to fit the model.
cnms
The names of the grouping factors and group specific parameters, collapsed across the longitudinal or glmer submodels.
flevels
The unique factor levels for each grouping factor, collapsed across the longitudinal or glmer submodels.
n_markers
The number of longitudinal or glmer submodels.
n_yobs
The number of observations for each longitudinal or glmer submodel.
n_grps
The 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).
runtime
The time taken to fit the model (in minutes).
id_var,time_var
The names of the variables distinguishing between individuals, and representing time in the longitudinal submodel.
n_subjects
The number of individuals.
n_events
The number of non-censored events.
eventtime,status
The event (or censoring) time and status indicator for each individual.
basehaz
A list containing information about the baseline hazard.
assoc
An array containing information about the association structure.
epsilon
The 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).
qnodes
The number of Gauss-Kronrod quadrature nodes used to evaluate the cumulative hazard in the joint likelihood function.