VD.A: Vargha and Delaney A measure

In effsize: Efficient Effect Size Computation

Description

Computes the Vargha and Delaney A effect size measure.

Usage

VD.A(d, ...)

## S3 method for class 'formula'
VD.A(formula,data=list(), ...)

## Default S3 method:
VD.A(d,f, ...)

Arguments

d	a numeric vector giving either the data values (if f is a factor) or the treatment group values (if f is a numeric vector)
f	either a factor with two levels or a numeric vector of values
formula	a formula of the form y ~ f, where y is a numeric variable giving the data values and f a factor with two levels giving the corresponding group
data	an optional matrix or data frame containing the variables in the formula formula. By default the variables are taken from environment(formula).
...	further arguments to be passed to or from methods.

Details

The function computes the Vargha and Delaney A effect size measure (Vargha and Delaney, 2000).

Value

A list of class effsize containing the following components:

estimate	the A statistics estimate
magnitude	a qualitative assessment of the magnitude of effect size
method	the method used, i.e. "Vargha and Delaney A"

Author(s)

Marco Torchiano http://softeng.polito.it/torchiano/

References

A. Vargha and H. D. Delaney. "A critique and improvement of the CL common language effect size statistics of McGraw and Wong." Journal of Educational and Behavioral Statistics, 25(2):101-132, 2000

See Also

cliff.delta, cohen.d, print.effsize

Examples

treatment = rnorm(100,mean=10)
control = rnorm(100,mean=12)
d = (c(treatment,control))
f = rep(c("Treatment","Control"),each=100)
## compute Vargha and Delaney A
## treatment and control
VD.A(treatment,control)
## data and factor
VD.A(d,f)
## formula interface
VD.A(d ~ f)

Example output

Vargha and Delaney A

A estimate: 0.0766 (large)

Vargha and Delaney A

A estimate: 0.9234 (large)

Vargha and Delaney A

A estimate: 0.9234 (large)

effsize documentation built on Oct. 23, 2020, 5:15 p.m.