R: Bonett-Seier test of scale for paired samples

bonettseier.Var.test

R Documentation

Bonett-Seier test of scale for paired samples

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.

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)