bonettseier.Var.test {PairedData} | 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.
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)