View source: R/stats-htest-tidiers.R
tidy.pairwise.htest | R Documentation |
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 class 'pairwise.htest'
tidy(x, ...)
x |
A |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in
|
Note that in one-sided tests, the alternative hypothesis of each test can be stated as "group1 is greater/less than group2".
Note also that the columns of group1 and group2 will always be a factor, even if the original input is (e.g.) numeric.
A tibble::tibble()
with columns:
group1 |
First group being compared. |
group2 |
Second group being compared. |
p.value |
The two-sided p-value associated with the observed statistic. |
stats::pairwise.t.test()
, stats::pairwise.wilcox.test()
,
tidy()
Other htest tidiers:
augment.htest()
,
tidy.htest()
,
tidy.power.htest()
attach(airquality)
Month <- factor(Month, labels = month.abb[5:9])
ptt <- pairwise.t.test(Ozone, Month)
tidy(ptt)
library(modeldata)
data(hpc_data)
attach(hpc_data)
ptt2 <- pairwise.t.test(compounds, class)
tidy(ptt2)
tidy(pairwise.t.test(compounds, class, alternative = "greater"))
tidy(pairwise.t.test(compounds, class, alternative = "less"))
tidy(pairwise.wilcox.test(compounds, class))
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