find_parameters.betamfx: Find names of model parameters from marginal effects models

In insight: Easy Access to Model Information for Various Model Objects

Find names of model parameters from marginal effects models

Description

Returns the names of model parameters, like they typically appear in the summary() output.

Usage

## S3 method for class 'betamfx'
find_parameters(
  x,
  component = c("all", "conditional", "precision", "marginal", "location",
    "distributional", "auxiliary"),
  flatten = FALSE,
  ...
)

## S3 method for class 'logitmfx'
find_parameters(
  x,
  component = c("all", "conditional", "marginal", "location"),
  flatten = FALSE,
  ...
)

Arguments

x	A fitted model.
component	Which type of parameters to return, such as parameters for the conditional model, the zero-inflated part of the model, the dispersion term, the instrumental variables or marginal effects be returned? Applies to models with zero-inflated and/or dispersion formula, or to models with instrumental variables (so called fixed-effects regressions), or models with marginal effects from mfx. May be abbreviated. Note that the conditional component is also called count or mean component, depending on the model. There are three convenient shortcuts: component = "all" returns all possible parameters. If component = "location", location parameters such as conditional, zero_inflated, smooth_terms, or instruments are returned (everything that are fixed or random effects - depending on the effects argument - but no auxiliary parameters). For component = "distributional" (or "auxiliary"), components like sigma, dispersion, beta or precision (and other auxiliary parameters) are returned.
flatten	Logical, if TRUE, the values are returned as character vector, not as list. Duplicated values are removed.
...	Currently not used.

Value

A list of parameter names. The returned list may have following elements:

• conditional, the "fixed effects" part from the model.

• marginal, the marginal effects.

• precision, the precision parameter.

Examples

data(mtcars)
m <- lm(mpg ~ wt + cyl + vs, data = mtcars)
find_parameters(m)

insight documentation built on Oct. 2, 2024, 9:07 a.m.