# Parameters from robust statistical objects in `WRS2`

Source: `R/methods_wrs2.R`

`model_parameters.t1way.Rd`

Parameters from robust statistical objects in `WRS2`

## Usage

```
# S3 method for class 't1way'
model_parameters(model, keep = NULL, verbose = TRUE, ...)
```

## Arguments

- model
Object from

`WRS2`

package.- keep
Character containing a regular expression pattern that describes the parameters that should be included (for

`keep`

) or excluded (for`drop`

) in the returned data frame.`keep`

may also be a named list of regular expressions. All non-matching parameters will be removed from the output. If`keep`

is a character vector, every parameter name in the*"Parameter"*column that matches the regular expression in`keep`

will be selected from the returned data frame (and vice versa, all parameter names matching`drop`

will be excluded). Furthermore, if`keep`

has more than one element, these will be merged with an`OR`

operator into a regular expression pattern like this:`"(one|two|three)"`

. If`keep`

is a named list of regular expression patterns, the names of the list-element should equal the column name where selection should be applied. This is useful for model objects where`model_parameters()`

returns multiple columns with parameter components, like in`model_parameters.lavaan()`

. Note that the regular expression pattern should match the parameter names as they are stored in the returned data frame, which can be different from how they are printed. Inspect the`$Parameter`

column of the parameters table to get the exact parameter names.- verbose
Toggle warnings and messages.

- ...
Arguments passed to or from other methods.

## Examples

```
if (require("WRS2") && packageVersion("WRS2") >= "1.1.3") {
model <- t1way(libido ~ dose, data = viagra)
model_parameters(model)
}
#> Loading required package: WRS2
#> A heteroscedastic one-way ANOVA for trimmed means
#>
#> F | df | df (error) | p | Estimate | 95% CI | Effectsize
#> ---------------------------------------------------------------------------------------------
#> 3.00 | 2 | 4 | 0.160 | 0.79 | [0.41, 1.36] | Explanatory measure of effect size
```