bonettseier.Var.test: Bonett-Seier test of scale for paired samples

In PairedData: Paired Data Analysis

Description

Robust test of scale for paired samples based on the mean absolute deviations.

Usage

bonettseier.Var.test(x, ...)

## Default S3 method:
bonettseier.Var.test(x, y = NULL, alternative = c("two.sided", "less", "greater"), 
omega = 1, conf.level = 0.95,...)

## S3 method for class 'paired'
bonettseier.Var.test(x, ...)

Arguments

x	first sample or object of class paired.
y	second sample.
alternative	alternative hypothesis.
omega	a priori ratio of means absolute deviations.
conf.level	confidence level.
...	further arguments to be passed to or from methods.

Value

A list with class "htest" containing the following components:

statistic	the value of the z-statistic.
p.value	the p-value for the test.
conf.int	a confidence interval for the ratio of means absolute deviations appropriate to the specified alternative hypothesis.
estimate	the estimated means absolute deviations.
null.value	the specified hypothesized value of the ratio of means absolute deviations.
alternative	a character string describing the alternative hypothesis.
method	a character string indicating what type of test was performed.
data.name	a character string giving the name(s) of the data.

Author(s)

Stephane CHAMPELY

References

Bonett, D.G. and Seier E. (2003) Statistical inference for a ratio of dispersions using paired samples. Journal of Educational and Behavioral Statistics, 28, 21-30.

See Also

Var.test, grambsch.Var.test

Examples

z<-rnorm(20)
x<-rnorm(20)+z
y<-(rnorm(20)+z)*2
bonettseier.Var.test(x,y)

data(anscombe2)
p<-with(anscombe2,paired(X1,Y1))
bonettseier.Var.test(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


	Paired Bonett-Seier test

data:  x and y
z = -3.2064, p-value = 0.001344
alternative hypothesis: true ratio of means absolute deviations is not equal to 1
95 percent confidence interval:
 0.2089073 0.6853880
sample estimates:
 mean abs. dev. of x  mean abs. dev. of y 
           0.7969132            2.1060369 


	Paired Bonett-Seier test

data:  X1 and Y1
z = -0.020766, p-value = 0.9834
alternative hypothesis: true ratio of means absolute deviations is not equal to 1
95 percent confidence interval:
 0.6478529 1.5295746
sample estimates:
 mean abs. dev. of x  mean abs. dev. of y 
            2.484667             2.496000 

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