insight (version 1.0.0)

find_interactions: Find interaction terms from models

Description

Returns all lowest to highest order interaction terms from a model.

Usage

find_interactions(
  x,
  component = c("all", "conditional", "zi", "zero_inflated", "dispersion", "instruments"),
  flatten = FALSE
)

Value

A list of character vectors that represent the interaction terms. Depending on component, the returned list has following elements (or NULL, if model has no interaction term):

• conditional, interaction terms that belong to the "fixed effects" terms from the model

• zero_inflated, interaction terms that belong to the "fixed effects" terms from the zero-inflation component of the model

• instruments, for fixed-effects regressions like ivreg, felm or plm, interaction terms that belong to the instrumental variables

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). See details in section Model Components .May be abbreviated. Note that the conditional component also refers to the count or mean component - names may differ, depending on the modeling package. There are three convenient shortcuts (not applicable to all model classes):

• 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.

Examples

data(mtcars)

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

m <- lm(mpg ~ wt * cyl + vs * hp * gear + carb, data = mtcars)
find_interactions(m)