Get group means and bootstrapped effect sizes from the `rcompanion::groupwiseMean` function. The function had to be taken separately from the package as the dependency is failing upon install of the current package.

From the original documentation: "Calculates means and confidence intervals for groups."

From: https://rcompanion.org/handbook/C_03.html

"For routine use, I recommend using bootstrapped confidence intervals, particularly the BCa or percentile methods (but...) by default, the function reports confidence intervals by the traditional method."

## Usage

``````rcompanion_groupwiseMean(
formula = NULL,
data = NULL,
var = NULL,
group = NULL,
trim = 0,
na.rm = FALSE,
conf = 0.95,
R = 5000,
boot = FALSE,
normal = FALSE,
basic = FALSE,
percentile = FALSE,
bca = FALSE,
digits = 3,
...
)``````

## Arguments

formula

A formula indicating the measurement variable and the grouping variables. e.g. y ~ x1 + x2.

data

The data frame to use.

var

The measurement variable to use. The name is in double quotes.

group

The grouping variable to use. The name is in double quotes. Multiple names are listed as a vector. (See example.)

trim

The proportion of observations trimmed from each end of the values before the mean is calculated. (As in `mean()`)

na.rm

If `TRUE`, `NA` values are removed during calculations. (As in `mean()`)

conf

The confidence interval to use.

R

The number of bootstrap replicates to use for bootstrapped statistics.

boot

If `TRUE`, includes the mean of the bootstrapped means. This can be used as an estimate of the mean for the group.

If `TRUE`, includes the traditional confidence intervals for the group means, using the t-distribution. If `trim` is not 0, the traditional confidence interval will produce `NA`. Likewise, if there are `NA` values that are not removed, the traditional confidence interval will produce `NA`.

normal

If `TRUE`, includes the normal confidence intervals for the group means by bootstrap. See `{boot::boot.ci}`.

basic

If `TRUE`, includes the basic confidence intervals for the group means by bootstrap. See `{boot::boot.ci}`.

percentile

If `TRUE`, includes the percentile confidence intervals for the group means by bootstrap. See `{boot::boot.ci}`.

bca

If `TRUE`, includes the BCa confidence intervals for the group means by bootstrap. See `{boot::boot.ci}`.

digits

The number of significant figures to use in output.

...

Other arguments passed to the `boot` function.

## Value

A data frame of requested statistics by group.

## Details

The input should include either `formula` and `data`; or `data`, `var`, and `group`. (See examples).

``````     Results for ungrouped (one-sample) data can be obtained by either
setting the right side of the formula to 1, e.g.  y ~ 1, or by
setting \code{group=NULL} when using \code{var}.``````

## Note

The parsing of the formula is simplistic. The first variable on the left side is used as the measurement variable. The variables on the right side are used for the grouping variables.

``````     In general, it is advisable to handle \code{NA} values before
using this function.
With some options, the function may not handle missing values well,
or in the manner desired by the user.
In particular, if \code{bca=TRUE} and there are \code{NA} values,
the function may fail.

For a traditional method to calculate confidence intervals
on trimmed means,
see Rand Wilcox, Introduction to Robust Estimation and
Hypothesis Testing.``````

## References

https://rcompanion.org/handbook/C_03.html

## Author

Salvatore Mangiafico, mangiafico@njaes.rutgers.edu

## Examples

``````# \donttest{
### Example with formula notation
data(mtcars)
rcompanion_groupwiseMean(mpg ~ factor(cyl),
data         = mtcars,
percentile   = TRUE
)
#>   cyl  n Mean Conf.level Percentile.lower Percentile.upper
#> 1   4 11 26.7       0.95             24.1             29.1
#> 2   6  7 19.7       0.95             18.7             20.7
#> 3   8 14 15.1       0.95             13.7             16.4

# Example with variable notation
data(mtcars)
rcompanion_groupwiseMean(
data = mtcars,
var = "mpg",
group = c("cyl", "am"),