mean_ci: Means and Confidence Intervals

In qwraps2: Quick Wraps 2

Means and Confidence Intervals

Description

A function for calculating and formatting means and confidence interval.

Usage

mean_ci(
  x,
  na_rm = FALSE,
  alpha = getOption("qwraps2_alpha", 0.05),
  qdist = stats::qnorm,
  qdist.args = list(),
  ...
)

## S3 method for class 'qwraps2_mean_ci'
print(x, ...)

Arguments

x	a numeric vector
na_rm	if true, omit NA values
alpha	defaults to getOption('qwraps2_alpha', 0.05). The symmetric 100(1-alpha)% CI will be determined.
qdist	defaults to qnorm. use qt for a Student t intervals.
qdist.args	list of arguments passed to qdist
...	arguments passed to frmtci.

Details

Given a numeric vector, mean_ci will return a vector with the mean, LCL, and UCL. Using frmtci will be helpful for reporting the results in print.

Value

a vector with the mean, lower confidence limit (LCL), and the upper confidence limit (UCL).

See Also

frmtci

Examples

# using the standard normal for the CI
mean_ci(mtcars$mpg)

# print it nicely
qwraps2::frmtci(mean_ci(mtcars$mpg))
qwraps2::frmtci(mean_ci(mtcars$mpg), show_level = TRUE)
qwraps2::frmtci(mean_ci(mtcars$mpg, alpha = 0.01), show_level = TRUE)

# Compare to the ci that comes form t.test
t.test(mtcars$mpg)
t.test(mtcars$mpg)$conf.int
mean_ci(mtcars$mpg, qdist = stats::qt, qdist.args = list(df = 31))

qwraps2 documentation built on Nov. 10, 2023, 1:06 a.m.