# Get group means and CIs (rcompanion::groupwiseMean)

Source:`R/rcompanion_groupwiseMean.R`

`rcompanion_groupwiseMean.Rd`

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,
traditional = TRUE,
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.- traditional
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.

## 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.
```

## Author

Salvatore Mangiafico, mangiafico@njaes.rutgers.edu

## Examples

```
# \donttest{
### Example with formula notation
data(mtcars)
rcompanion_groupwiseMean(mpg ~ factor(cyl),
data = mtcars,
traditional = FALSE,
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"),
traditional = FALSE,
percentile = TRUE
)
#> cyl am n Mean Conf.level Percentile.lower Percentile.upper
#> 1 4 0 3 22.9 0.95 21.5 24.4
#> 2 4 1 8 28.1 0.95 25.0 30.9
#> 3 6 0 4 19.1 0.95 18.0 20.6
#> 4 6 1 3 20.6 0.95 19.7 21.0
#> 5 8 0 12 15.0 0.95 13.5 16.5
#> 6 8 1 2 15.4 0.95 15.0 15.8
# }
```