Tidy a(n) glmRob object

Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

Usage

# S3 method for class 'glmRob'
tidy(x, ...)

Arguments

x

A glmRob object returned from robust::glmRob().

...

Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.lvel = 0.9, all computation will proceed using conf.level = 0.95. Two exceptions here are:

• tidy() methods will warn when supplied an exponentiate argument if it will be ignored.

• augment() methods will warn when supplied a newdata argument if it will be ignored.

Details

For tidiers for robust models from the MASS package see tidy.rlm().

See also

robust::glmRob()

Other robust tidiers: augment.lmRob(), glance.glmRob(), glance.lmRob(), tidy.lmRob()

Examples

# load libraries for models and data
library(robust)

# fit model
gm <- glmRob(am ~ wt, data = mtcars, family = "binomial")

# summarize model fit with tidiers
tidy(gm)
#> # A tibble: 2 × 5
#>   term        estimate std.error statistic p.value
#>   <chr>          <dbl>     <dbl>     <dbl>   <dbl>
#> 1 (Intercept)    12.0       4.51      2.67 0.00759
#> 2 wt             -4.02      1.44     -2.80 0.00509
glance(gm)
#> # A tibble: 1 × 5
#>   deviance sigma null.deviance df.residual  nobs
#>      <dbl> <dbl>         <dbl>       <int> <int>
#> 1     19.2 0.800          44.4          30    32