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 summary.manova
tidy(x, ...)

## Arguments

x A summary.manova object return from stats::summary.manova(). 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

Depending on which test statistic was calculated when the object was created, only one of pillai, wilks, hl or roy is included.

tidy(), stats::summary.manova()

Other anova tidiers: glance.aov(), tidy.TukeyHSD(), tidy.anova(), tidy.aovlist(), tidy.aov(), tidy.manova()

## Value

A tibble::tibble() with columns:

den.df

Degrees of freedom of the denominator

num.df

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.

term

The name of the regression term.

pillai

Pillai's trace.

wilks

Wilk's lambda.

hl

Hotelling-Lawley trace.

roy

Roy's greatest root.

## Examples


npk2 <- within(npk, foo <- rnorm(24))

m <- summary(
manova(cbind(yield, foo) ~ block + N * P * K, npk2),
test = "Wilks"
)

tidy(m)#> # A tibble: 8 x 7
#>   term         df  wilks statistic num.df den.df  p.value
#>   <chr>     <dbl>  <dbl>     <dbl>  <dbl>  <dbl>    <dbl>
#> 1 block         5  0.147     3.54      10     22  0.00646
#> 2 N             1  0.491     5.70       2     11  0.0200
#> 3 P             1  0.956     0.254      2     11  0.780
#> 4 K             1  0.563     4.27       2     11  0.0424
#> 5 N:P           1  0.894     0.651      2     11  0.540
#> 6 N:K           1  0.311    12.2        2     11  0.00162
#> 7 P:K           1  0.808     1.31       2     11  0.309
#> 8 Residuals    12 NA        NA         NA     NA NA