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 anova
tidy(x, ...)

## Arguments

x An anova objects, such as those created by stats::anova() or car::Anova(). 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.

## Details

The term column of an ANOVA table can come with leading or trailing whitespace, which this tidying method trims.

tidy(), stats::anova(), car::Anova()

Other anova tidiers: tidy.TukeyHSD, tidy.aovlist, tidy.aov, tidy.manova

## Value

A tibble::tibble() with columns:

df

Degrees of freedom used by this term in the model.

meansq

Mean sum of squares. Equal to total sum of squares divided by degrees of freedom.

p.value

The two-sided p-value associated with the observed statistic.

statistic

The value of a T-statistic to use in a hypothesis that the regression term is non-zero.

sumsq

Sum of squares explained by this term

term

The name of the regression term.

## Examples


a <- anova(lm(mpg ~ wt + qsec + disp, mtcars))
tidy(a)#> # A tibble: 4 x 6
#>   term         df     sumsq    meansq  statistic   p.value
#>   <chr>     <int>     <dbl>     <dbl>      <dbl>     <dbl>
#> 1 wt            1 848.      848.      121.        1.08e-11
#> 2 qsec          1  82.9      82.9      11.9       1.82e- 3
#> 3 disp          1   0.00102   0.00102   0.000147  9.90e- 1
#> 4 Residuals    28 195.        6.98     NA        NA