effect.size: Effect size computations for paired data

In PairedData: Paired Data Analysis

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)

Example output

Loading required package: MASS
Loading required package: gld
Loading required package: mvtnorm
Loading required package: lattice
Loading required package: ggplot2

Attaching package: 'PairedData'

The following object is masked from 'package:base':

    summary

          Average Single (x) Single (y) Difference
OLS    -0.9163387 -0.7830338 -1.1539888 -0.9288940
Robust -0.8319184 -0.7485306 -0.9512856 -0.9445462

PairedData documentation built on May 1, 2019, 6:49 p.m.