Get predicted values from a model object (internal function)
get_predict(model, newdata, type, ...)# S3 method for default
get_predict(
model,
newdata = insight::get_data(model),
type = "response",
conf.level = NULL,
...
)
# S3 method for polr
get_predict(
model,
newdata = insight::get_data(model),
type = "probs",
conf.level = NULL,
...
)
# S3 method for glmmPQL
get_predict(
model,
newdata = insight::get_data(model),
type = "response",
conf.level = NULL,
...
)
# S3 method for glimML
get_predict(model, newdata = insight::get_data(model), type = "response", ...)
# S3 method for multinom
get_predict(model, newdata = insight::get_data(model), type = "probs", ...)
# S3 method for brmultinom
get_predict(model, newdata = insight::get_data(model), type = "probs", ...)
# S3 method for brmsfit
get_predict(model, newdata = insight::get_data(model), type = "response", ...)
# S3 method for crch
get_predict(model, newdata = NULL, type = "location", ...)
# S3 method for fixest
get_predict(
model,
newdata = insight::get_data(model),
type = "response",
conf.level = NULL,
...
)
# S3 method for merMod
get_predict(
model,
newdata = insight::get_data(model),
type = "response",
conf.level = NULL,
...
)
# S3 method for lmerModLmerTest
get_predict(
model,
newdata = insight::get_data(model),
type = "response",
conf.level = NULL,
...
)
# S3 method for lmerMod
get_predict(
model,
newdata = insight::get_data(model),
type = "response",
conf.level = NULL,
...
)
# S3 method for mblogit
get_predict(model, newdata = insight::get_data(model), type = "probs", ...)
# S3 method for clm
get_predict(model, newdata = insight::get_data(model), type = "response", ...)
# S3 method for rq
get_predict(
model,
newdata = insight::get_data(model),
type = NULL,
conf.level = NULL,
...
)
# S3 method for rlmerMod
get_predict(model, newdata = insight::get_data(model), ...)
# S3 method for stanreg
get_predict(model, newdata = insight::get_data(model), type = "response", ...)
# S3 method for coxph
get_predict(
model,
newdata = insight::get_data(model),
type = "lp",
conf.level = NULL,
...
)
Model object
A dataset over which to compute marginal effects. NULL
uses
the original data used to fit the model.
Type(s) of prediction as string or character vector. This can differ based on the model type, but will typically be a string such as: "response", "link", "probs", or "zero".
The "Model-Specific Arguments" section below gives a list of arguments which can modify the behavior of this function for certain models (e.g., mixed-effects or bayesian).
A vector of predicted values of length equal to the number of rows
in newdata
. For models with multi-level outcomes (e.g., multinomial
logit), this function returns a matrix of predicted values with column names
equal to each of the levels/groups.