wilcoxonPS: Grissom and Kim's Probability of Superiority (PS)

View source: R/wilcoxonPS.r

wilcoxonPSR Documentation

Grissom and Kim's Probability of Superiority (PS)

Description

Calculates Grissom and Kim's Probability of Superiority (PS) with confidence intervals by bootstrap

Usage

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

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.

digits

The number of significant digits in the output.

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.

verbose

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

...

Additional arguments, not used.

Details

PS 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.

PS is defined as P(Ya > Yb), with no provision made for tied values across groups.

If there are no tied values, PS will be equal to VDA.

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

Value

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

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.

Author(s)

Salvatore Mangiafico, mangiafico@njaes.rutgers.edu

References

Grissom, R.J. and J.J. Kim. 2012. Effect Sizes for Research. 2nd ed. Routledge, New York.

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

See Also

cliffDelta, vda

Examples

data(Catbus)
wilcoxonPS(Steps ~ Gender, data=Catbus, verbose=TRUE)


rcompanion documentation built on May 29, 2024, 8:42 a.m.