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Vargha and Delaney's A

vda.Rd

Calculates Vargha and Delaney's A (VDA) with confidence intervals by bootstrap

Usage

vda(
  formula = NULL,
  data = NULL,
  x = NULL,
  y = NULL,
  ci = FALSE,
  conf = 0.95,
  type = "perc",
  R = 1000,
  histogram = FALSE,
  reportIncomplete = FALSE,
  brute = FALSE,
  verbose = FALSE,
  digits = 3,
  ...
)

Arguments

formula

A formula indicating the response variable and the independent variable. e.g. y ~ group.

data

The data frame to use.

x

If no formula is given, the response variable for one group.

y

The response variable for the other group.

ci

If TRUE, returns confidence intervals by bootstrap. May be slow.

conf

The level for the confidence interval.

type

The type of confidence interval to use. Can be any of "norm", "basic", "perc", or "bca". Passed to boot.ci.

R

The number of replications to use for bootstrap.

histogram

If TRUE, produces a histogram of bootstrapped values.

reportIncomplete

If FALSE (the default), NA will be reported in cases where there are instances of the calculation of the statistic failing during the bootstrap procedure.

brute

If FALSE, the default, the statistic is based on the U statistic from the wilcox.test function. If TRUE, the function will compare values in the two samples directly.

verbose

If TRUE, reports the proportion of ties and the proportions of (Ya > Yb) and (Ya < Yb).

digits

The number of significant digits in the output.

...

Additional arguments passed to the wilcox.test function.

Value

A single statistic, VDA. Or a small data frame consisting of VDA, and the lower and upper confidence limits.

Details

VDA is an effect size statistic appropriate in cases where a Wilcoxon-Mann-Whitney test might be used. It ranges from 0 to 1, with 0.5 indicating stochastic equality, and 1 indicating that the first group dominates the second.

By default, the function calculates VDA from the "W" U statistic from the wilcox.test function. Specifically, VDA = U/(n1*n2).

The input should include either formula and data; or x, and y. If there are more than two groups, only the first two groups are used.

Currently, the function makes no provisions for NA values in the data. It is recommended that NAs be removed beforehand.

When the data in the first group are greater than in the second group, VDA is greater than 0.5. When the data in the second group are greater than in the first group, VDA is less than 0.5.

Be cautious with this interpretation, as R will alphabetize groups in the formula interface if the grouping variable is not already a factor.

When VDA is close to 0 or close to 1, or with small sample size, the confidence intervals determined by this method may not be reliable, or the procedure may fail.

Note

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

References

https://rcompanion.org/handbook/F_04.html

See also

cliffDelta, multiVDA

Author

Salvatore Mangiafico, mangiafico@njaes.rutgers.edu

Examples

data(Catbus)
vda(Steps ~ Gender, data=Catbus)
#>   VDA 
#> 0.773