Get levels of the outcome variable in grouped or multivariate models
get_group_names(model, ...)# S3 method for default
get_group_names(model, ...)
# S3 method for polr
get_group_names(model, ...)
# S3 method for multinom
get_group_names(model, ...)
# S3 method for bracl
get_group_names(model, ...)
# S3 method for brmsfit
get_group_names(model, ...)
# S3 method for mblogit
get_group_names(model, type, ...)
# S3 method for clm
get_group_names(model, ...)
# S3 method for hurdle
get_group_names(model, type = "count", ...)
A character vector
Model object
Additional arguments are passed to the predict() method
supplied by the modeling package.These arguments are particularly useful
for mixed-effects or bayesian models (see the online vignettes on the
marginaleffects website). Available arguments can vary from model to
model, depending on the range of supported arguments by each modeling
package. See the "Model-Specific Arguments" section of the
?marginaleffects documentation for a non-exhaustive list of available
arguments.
string indicates the type (scale) of the predictions used to
compute marginal effects or contrasts. This can differ based on the model
type, but will typically be a string such as: "response", "link", "probs",
or "zero". When an unsupported string is entered, the model-specific list of
acceptable values is returned in an error message. When type is NULL, the
default value is used. This default is the first model-related row in
the marginaleffects:::type_dictionary dataframe.