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

`TRUE`

, the values are returned as character vector, not as list. Duplicated values are removed.- 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 like`ivreg`

,`felm`

or`plm`

, the instrumental variables`correlation`

, for models with correlation-component like`gls`

, 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 as`conditional`

,`zero_inflated`

,`smooth_terms`

, or`instruments`

(everything that are fixed or random effects - depending on the`effects`

argument - but no auxiliary parameters).`"distributional"`

(or`"auxiliary"`

): components like`sigma`

,`dispersion`

,`beta`

or`precision`

(and other auxiliary parameters) are returned.