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 manova tidy(x, test = "Pillai", ...)
x | A |
---|---|
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
|
Depending on which test statistic is specified 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()
A tibble::tibble()
with columns:
Degrees of freedom of the denominator.
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 name of the regression term.
Pillai's trace.
Wilk's lambda.
Hotelling-Lawley trace.
Roy's greatest root.
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 0.889 1.92 10 24 0.0925 #> 2 N 1 0.521 5.97 2 11 0.0175 #> 3 P 1 0.0505 0.293 2 11 0.752 #> 4 K 1 0.357 3.05 2 11 0.0882 #> 5 N:P 1 0.103 0.633 2 11 0.549 #> 6 N:K 1 0.294 2.29 2 11 0.147 #> 7 P:K 1 0.00855 0.0474 2 11 0.954 #> 8 Residuals 12 NA NA NA NA NA