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.
# S3 method for glm tidy(x, conf.int = FALSE, conf.level = 0.95, exponentiate = FALSE, ...)
x | A |
---|---|
conf.int | Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to |
conf.level | The confidence level to use for the confidence interval
if |
exponentiate | Logical indicating whether or not to exponentiate the
the coefficient estimates. This is typical for logistic and multinomial
regressions, but a bad idea if there is no log or logit link. Defaults
to |
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
Other lm tidiers:
augment.glm()
,
augment.lm()
,
glance.glm()
,
glance.lm()
,
glance.summary.lm()
,
glance.svyglm()
,
tidy.lm.beta()
,
tidy.lm()
,
tidy.mlm()
,
tidy.summary.lm()