broom (version 0.7.5)

tidy.htest: Tidy/glance a(n) htest object

Description

For models that have only a single component, the tidy() and glance() methods are identical. Please see the documentation for both of those methods.

Usage

# S3 method for htest
tidy(x, ...)
# S3 method for htest
glance(x, ...)

Arguments

x

An htest objected, such as those created by stats::cor.test(), stats::t.test(), stats::wilcox.test(), stats::chisq.test(), etc.

...

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.level = 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.

Value

A tibble::tibble() with columns:

alternative

Alternative hypothesis (character).

conf.high

Upper bound on the confidence interval for the estimate.

conf.low

Lower bound on the confidence interval for the estimate.

estimate

The estimated value of the regression term.

estimate1

Sometimes two estimates are computed, such as in a two-sample t-test.

estimate2

Sometimes two estimates are computed, such as in a two-sample t-test.

method

Method used.

p.value

The two-sided p-value associated with the observed statistic.

parameter

The parameter being modeled.

statistic

The value of a T-statistic to use in a hypothesis that the regression term is non-zero.

See Also

tidy(), stats::cor.test(), stats::t.test(), stats::wilcox.test(), stats::chisq.test()

Other htest tidiers: augment.htest(), tidy.pairwise.htest(), tidy.power.htest()

Examples

# NOT RUN {
tt <- t.test(rnorm(10))
tidy(tt)
glance(tt) # same output for all htests

tt <- t.test(mpg ~ am, data = mtcars)
tidy(tt)

wt <- wilcox.test(mpg ~ am, data = mtcars, conf.int = TRUE, exact = FALSE)
tidy(wt)

ct <- cor.test(mtcars$wt, mtcars$mpg)
tidy(ct)

chit <- chisq.test(xtabs(Freq ~ Sex + Class, data = as.data.frame(Titanic)))
tidy(chit)
augment(chit)
# }