prior_summary method provides a summary of the prior distributions
used for the parameters in a given model. In some cases the user-specified
prior does not correspond exactly to the prior used internally by
rstap (see the sections below). Especially in these cases, but also
in general, it can be much more useful to visualize the priors.
# S3 method for stapreg prior_summary(object, digits = 2, ...)
A fitted model object returned by one of the
rstap modeling functions. See
Number of digits to use for rounding.
Currently ignored by the method for stapreg objects.
A list of class "prior_summary.stapreg", which has its own print method.
For rstap modeling functions that accept a
argument, the specified prior for the intercept term applies to the
intercept after rstap internally centers the predictors so they
each have mean zero. The estimate of the intercept returned to the user
correspond to the intercept with the predictors as specified by the user
(unmodified by rstap), but when specifying the prior the
intercept can be interpreted as the expected outcome when the predictors are
set to their means.
For some models you may see "
in the printed output and adjusted scales included in the object returned
prior_summary. These adjusted scale values are the prior scales
actually used by rstap and are computed by adjusting the prior
scales specified by the user to account for the scales of the predictors
(as described in the documentation for the
argument). To disable internal prior scale adjustments set the
autoscale argument to
FALSE when setting a prior using one of
the distributions that accepts an
autoscale argument. For example,
normal(0, 5, autoscale=FALSE) instead of just
Note that for prior_stap all priors are set on the scaled covariates this is
done so that multiple priors placed on differing staps can be roughly comparable.
If only one prior was specified this will be returned in a section entitled "STAP scales". Otherwise no priors will be printed out. A more structured system for STAP prior printing is planned for the next release.
The priors help page and the Prior Distributions vignette from the rstanarm package.