find_predictors {insight} | R Documentation |
Find names of model predictors
Description
Returns the names of the predictor variables for the
different parts of a model (like fixed or random effects, zero-inflated
component, ...). Unlike find_parameters()
, the names from
find_predictors()
match the original variable names from the data
that was used to fit the model.
Usage
find_predictors(x, ...)
## Default S3 method:
find_predictors(
x,
effects = c("fixed", "random", "all"),
component = c("all", "conditional", "zi", "zero_inflated", "dispersion", "instruments",
"correlation", "smooth_terms"),
flatten = FALSE,
verbose = TRUE,
...
)
## S3 method for class 'afex_aov'
find_predictors(
x,
effects = c("fixed", "random", "all"),
component = c("all", "conditional", "zi", "zero_inflated", "dispersion", "instruments",
"correlation", "smooth_terms"),
flatten = FALSE,
verbose = TRUE,
...
)
Arguments
x |
A fitted model. |
... |
Currently not used. |
effects |
Should variables for fixed effects, random effects or both be returned? Only applies to mixed models. May be abbreviated. |
component |
Should all predictor variables, predictor variables for the conditional model, the zero-inflated part of the model, the dispersion term or the instrumental variables be returned? Applies to models with zero-inflated and/or dispersion formula, or to models with instrumental variable (so called fixed-effects regressions). May be abbreviated. Note that the conditional component is also called count or mean component, depending on the model. |
flatten |
Logical, if |
verbose |
Toggle warnings. |
Value
A list of character vectors that represent the name(s) of the
predictor variables. Depending on the combination of the arguments
effects
and component
, the returned list has following elements:
-
conditional
, the "fixed effects" terms from the model -
random
, the "random effects" terms from the model -
zero_inflated
, the "fixed effects" terms from the zero-inflation component of the model -
zero_inflated_random
, the "random effects" terms from the zero-inflation component of the model -
dispersion
, the dispersion terms -
instruments
, for fixed-effects regressions likeivreg
,felm
orplm
, the instrumental variables -
correlation
, for models with correlation-component likegls
, the variables used to describe the correlation structure
Model components
Possible values for the component
argument depend on the model class.
Following are valid options:
-
"all"
: returns all model components, applies to all models, but will only have an effect for models with more than just the conditional model component. -
"conditional"
: only returns the conditional component, i.e. "fixed effects" terms from the model. Will only have an effect for models with more than just the conditional model component. -
"smooth_terms"
: returns smooth terms, only applies to GAMs (or similar models that may contain smooth terms). -
"zero_inflated"
(or"zi"
): returns the zero-inflation component. -
"dispersion"
: returns the dispersion model component. This is common for models with zero-inflation or that can model the dispersion parameter. -
"instruments"
: for instrumental-variable or some fixed effects regression, returns the instruments. -
"location"
: returns location parameters such asconditional
,zero_inflated
,smooth_terms
, orinstruments
(everything that are fixed or random effects - depending on theeffects
argument - but no auxiliary parameters). -
"distributional"
(or"auxiliary"
): components likesigma
,dispersion
,beta
orprecision
(and other auxiliary parameters) are returned.
Examples
data(mtcars)
m <- lm(mpg ~ wt + cyl + vs, data = mtcars)
find_predictors(m)