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 cross models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

# S3 method for glmRob
tidy(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. Additionally, if you pass newdata = my_tibble to an augment() method that does not accept a newdata argument, it will use the default value for the data argument.


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

See also


library(robust) gm <- glmRob(am ~ wt, data = mtcars, family = "binomial") tidy(gm)
#> # A tibble: 2 x 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
#> # A tibble: 1 x 5 #> deviance sigma null.deviance df.residual nobs #> <dbl> <dbl> <dbl> <int> <int> #> 1 19.2 0.800 44.4 30 32