get_predict: Get predicted values from a model object (internal function)

Description

Get predicted values from a model object (internal function)

Usage

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,
  ...
)

Arguments

model

Model object

newdata

A dataset over which to compute marginal effects. NULL uses the original data used to fit the model.

type

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".

...

Additional arguments are passed to the predict() method used to compute adjusted predictions. 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 document for a non-exhaustive list of available arguments.

Value

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.