broom (version 0.5.6)

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.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.

Value

A one-row tibble::tibble with one or more of the following columns, depending on which hypothesis test was used.

estimate

Estimate of the effect size

statistic

Test statistic used to compute the p-value

p.value

P-value

parameter

Parameter field in the htest, typically degrees of freedom

conf.low

Lower bound on a confidence interval

conf.high

Upper bound on a confidence interval

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 to compute the statistic as a string

alternative

Alternative hypothesis as a string

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)

# }