effect.size {PairedData}

Effect size computations for paired data

Description

Robust and classical effects sizes for paired samples of the form: (Mx-My)/S where Mx and My are location parameters for each sample and S is a scale parameter

Usage

## S4 method for signature 'paired'
effect.size(object,tr=0.2)

Arguments

object

an object of class paired

tr

percentage of trimming

Value

A table with two rows corresponding to classical (means) and robust (trimmed means, tr=0.2) delta-type effect sizes. The four columns correspond to:

Average

Numerator is the difference in (trimmed) means, denominator is the average of the two (winsorised and rescaled to be consistent with the standard deviation when the distribution is normal) standard deviations

Single (x)

Denominator is the (winsorised and rescaled) standard deviation of the first sample

Single (y)

Denominator is the (winsorised and rescaled) standard deviation of the second sample

Difference

Numerator is the (trimmed) mean and denominator the (winsorised and rescaled) standard deviation of the differences (x-y)

Author(s)

Stephane CHAMPELY

References

Algina, J., Keselman, H.J. and Penfield, R.D. (2005) Effects sizes and their intervals: the two-level repeated measures case. Educational and Psychological Measurement, 65, 241-258.

Examples

z<-rnorm(20)
x<-rnorm(20)+z
y<-rnorm(20)+z+1
p<-paired(x,y)
effect.size(p)