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 aovlist
tidy(x, ...)
An aovlist
objects, such as those created by stats::aov()
.
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.
A tibble::tibble()
with columns:
Degrees of freedom used by this term in the model.
Mean sum of squares. Equal to total sum of squares divided by degrees of freedom.
The two-sided p-value associated with the observed statistic.
The value of a T-statistic to use in a hypothesis that the regression term is non-zero.
The error stratum.
Sum of squares explained by this term.
The name of the regression term.
The term
column of an ANOVA table can come with leading or
trailing whitespace, which this tidying method trims.
For documentation on the tidier for car::leveneTest()
output, see
tidy.leveneTest()
Other anova tidiers:
glance.aov()
,
tidy.TukeyHSD()
,
tidy.anova()
,
tidy.aov()
,
tidy.manova()
# NOT RUN {
a <- aov(mpg ~ wt + qsec + Error(disp / am), mtcars)
tidy(a)
# }
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