View source: R/rcompanion_groupwiseMean.R
rcompanion_groupwiseMean | R Documentation |
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."
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,
...
)
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 |
na.rm |
If |
conf |
The confidence interval to use. |
R |
The number of bootstrap replicates to use for bootstrapped statistics. |
boot |
If |
traditional |
If |
normal |
If |
basic |
If |
percentile |
If |
bca |
If |
digits |
The number of significant figures to use in output. |
... |
Other arguments passed to the |
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}.
A data frame of requested statistics by group.
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.
Salvatore Mangiafico, mangiafico@njaes.rutgers.edu
https://rcompanion.org/handbook/C_03.html
### Example with formula notation
data(mtcars)
rcompanion_groupwiseMean(mpg ~ factor(cyl),
data = mtcars,
traditional = FALSE,
percentile = TRUE
)
# Example with variable notation
data(mtcars)
rcompanion_groupwiseMean(
data = mtcars,
var = "mpg",
group = c("cyl", "am"),
traditional = FALSE,
percentile = TRUE
)
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