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.
Usage
# S3 method for class 'manova'
tidy(x, test = "Pillai", ...)
Arguments
- x
A
manova
object return fromstats::manova()
.- test
One of "Pillai" (Pillai's trace), "Wilks" (Wilk's lambda), "Hotelling-Lawley" (Hotelling-Lawley trace) or "Roy" (Roy's greatest root) indicating which test statistic should be used. Defaults to "Pillai".
- ...
Arguments passed on to
stats::summary.manova
object
An object of class
"manova"
or anaov
object with multiple responses.intercept
logical. If
TRUE
, the intercept term is included in the table.tol
tolerance to be used in deciding if the residuals are rank-deficient: see
qr
.
Details
Depending on which test statistic is specified only one of pillai
,
wilks
, hl
or roy
is included.
See also
tidy()
, stats::summary.manova()
Other anova tidiers:
glance.anova()
,
glance.aov()
,
tidy.TukeyHSD()
,
tidy.anova()
,
tidy.aov()
,
tidy.aovlist()
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 <- manova(cbind(yield, foo) ~ block + N * P * K, npk2)
tidy(m)
#> # A tibble: 8 × 7
#> term df pillai statistic num.df den.df p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 block 5 0.909 2.00 10 24 0.0796
#> 2 N 1 0.601 8.29 2 11 0.00638
#> 3 P 1 0.237 1.71 2 11 0.226
#> 4 K 1 0.343 2.87 2 11 0.0993
#> 5 N:P 1 0.104 0.642 2 11 0.545
#> 6 N:K 1 0.214 1.50 2 11 0.266
#> 7 P:K 1 0.0705 0.417 2 11 0.669
#> 8 Residuals 12 NA NA NA NA NA