Parameters from robust statistical objects in WRS2 — model

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.

Value

A data frame of indices related to the model's parameters.

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 | [0.36, 1.95] | Explanatory measure of effect size