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 aovlist
tidy(x, ...)

## Arguments

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.

## Details

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

tidy(), stats::aov()

Other anova tidiers: tidy.TukeyHSD, tidy.anova, 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.

stratum

The error stratum

sumsq

Sum of squares explained by this term

term

The name of the regression term.

## Examples


a <- aov(mpg ~ wt + qsec + Error(disp / am), mtcars)
tidy(a)#> # A tibble: 5 x 7
#>   stratum term         df   sumsq  meansq statistic  p.value
#>   <chr>   <chr>     <dbl>   <dbl>   <dbl>     <dbl>    <dbl>
#> 1 disp    wt            1 809.    809.        NA    NA
#> 2 disp:am wt            1   0.389   0.389     NA    NA
#> 3 Within  wt            1  87.2    87.2       12.0   0.00176
#> 4 Within  qsec          1  34.2    34.2        4.72  0.0387
#> 5 Within  Residuals    27 195.      7.24      NA    NA