Returns the formula(s) for the different parts of a model
(like fixed or random effects, zero-inflated component, ...).
`formula_ok()`

checks if a model formula has valid syntax
regarding writing `TRUE`

instead of `T`

inside `poly()`

and that no data names are used (i.e. no `data$variable`

, but rather
`variable`

).

## Value

A list of formulas that describe the model. For simple models,
only one list-element, `conditional`

, is returned. For more complex
models, the returned list may have following elements:

`conditional`

, the "fixed effects" part from the model (in the context of fixed-effects or instrumental variable regression, also called*regressors*) . One exception are`DirichletRegModel`

models from DirichletReg, which has two or three components, depending on`model`

.`random`

, the "random effects" part from the model (or the`id`

for gee-models and similar)`zero_inflated`

, the "fixed effects" part from the zero-inflation component of the model`zero_inflated_random`

, the "random effects" part from the zero-inflation component of the model`dispersion`

, the dispersion formula`instruments`

, for fixed-effects or instrumental variable regressions like`ivreg::ivreg()`

,`lfe::felm()`

or`plm::plm()`

, the instrumental variables`cluster`

, for fixed-effects regressions like`lfe::felm()`

, the cluster specification`correlation`

, for models with correlation-component like`nlme::gls()`

, the formula that describes the correlation structure`slopes`

, for fixed-effects individual-slope models like`feisr::feis()`

, the formula for the slope parameters`precision`

, for`DirichletRegModel`

models from DirichletReg, when parametrization (i.e.`model`

) is`"alternative"`

.

## Note

For models of class `lme`

or `gls`

the correlation-component
is only returned, when it is explicitly defined as named argument
(`form`

), e.g. `corAR1(form = ~1 | Mare)`

## Examples

```
data(mtcars)
m <- lm(mpg ~ wt + cyl + vs, data = mtcars)
find_formula(m)
#> $conditional
#> mpg ~ wt + cyl + vs
#> <environment: 0x55ec2afd0078>
#>
#> attr(,"class")
#> [1] "insight_formula" "list"
m <- lme4::lmer(Sepal.Length ~ Sepal.Width + (1 | Species), data = iris)
f <- find_formula(m)
f
#> $conditional
#> Sepal.Length ~ Sepal.Width
#> <environment: 0x55ec2afd0078>
#>
#> $random
#> ~1 | Species
#> <environment: 0x55ec2b7ac9a0>
#>
#> attr(,"class")
#> [1] "insight_formula" "list"
format(f)
#> [1] "Sepal.Length ~ Sepal.Width + (~1 | Species)"
```