This functions tries to get the data that was used to fit the model and returns it as data frame.

## Usage

```
get_data(x, ...)
# S3 method for gee
get_data(x, effects = c("all", "fixed", "random"), verbose = TRUE, ...)
# S3 method for rqss
get_data(
x,
component = c("all", "conditional", "smooth_terms"),
verbose = TRUE,
...
)
# S3 method for hurdle
get_data(
x,
component = c("all", "conditional", "zi", "zero_inflated", "dispersion"),
verbose = TRUE,
...
)
# S3 method for zcpglm
get_data(
x,
component = c("all", "conditional", "zi", "zero_inflated"),
verbose = TRUE,
...
)
# S3 method for glmmTMB
get_data(
x,
effects = c("all", "fixed", "random"),
component = c("all", "conditional", "zi", "zero_inflated", "dispersion"),
verbose = TRUE,
...
)
# S3 method for merMod
get_data(x, effects = c("all", "fixed", "random"), verbose = TRUE, ...)
# S3 method for glmmadmb
get_data(x, effects = c("all", "fixed", "random"), verbose = TRUE, ...)
# S3 method for rlmerMod
get_data(x, effects = c("all", "fixed", "random"), ...)
# S3 method for clmm
get_data(x, effects = c("all", "fixed", "random"), ...)
# S3 method for mixed
get_data(x, effects = c("all", "fixed", "random"), ...)
# S3 method for afex_aov
get_data(x, shape = c("long", "wide"), ...)
# S3 method for lme
get_data(x, effects = c("all", "fixed", "random"), ...)
# S3 method for MixMod
get_data(
x,
effects = c("all", "fixed", "random"),
component = c("all", "conditional", "zi", "zero_inflated", "dispersion"),
verbose = TRUE,
...
)
# S3 method for brmsfit
get_data(x, effects = "all", component = "all", verbose = TRUE, ...)
# S3 method for stanreg
get_data(x, effects = c("all", "fixed", "random"), verbose = TRUE, ...)
# S3 method for MCMCglmm
get_data(x, effects = c("all", "fixed", "random"), verbose = TRUE, ...)
```

## Arguments

- x
A fitted model.

- ...
Currently not used.

- effects
Should model data for fixed effects, random effects or both be returned? Only applies to mixed models.

- verbose
Toggle messages and warnings.

- 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.- shape
Return long or wide data? Only applicable in repeated measures designs.

## Note

Unlike `model.frame()`

, which may contain transformed variables
(e.g. if `poly()`

or `scale()`

was used inside the formula to
specify the model), `get_data()`

aims at returning the "original",
untransformed data (if possible). Consequently, column names are changed
accordingly, i.e. `"log(x)"`

will become `"x"`

etc. for all data
columns with transformed values.

## Examples

```
if (require("lme4")) {
data(cbpp, package = "lme4")
cbpp$trials <- cbpp$size - cbpp$incidence
m <- glm(cbind(incidence, trials) ~ period, data = cbpp, family = binomial)
head(get_data(m))
}
#> cbind(incidence, trials).incidence cbind(incidence, trials).trials period
#> 1 2 12 1
#> 2 3 9 2
#> 3 4 5 3
#> 4 0 5 4
#> 5 3 19 1
#> 6 1 17 2
#> incidence trials
#> 1 2 12
#> 2 3 9
#> 3 4 5
#> 4 0 5
#> 5 3 19
#> 6 1 17
```