PairedData (version 0.9.1)

bonett.seier.test: Bonett-Seier test of scale for paired samples

Description

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

Usage

bonett.seier.test(x, ...)

## S3 method for class 'default':
bonett.seier.test(x, y = NULL, alternative = c("two.sided", "less", "greater"), 
omega = 1, conf.level = 0.95,...)

## S3 method for class 'paired':
bonett.seier.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 t-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.

References

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

See Also

var.test, pitman.morgan.test, grambsch.test

Examples

z<-rnorm(20)
x<-rnorm(20)+z
y<-(rnorm(20)+z)*2
bonett.seier.test(x,y)

data(anscombe2)
p<-with(anscombe2,paired(X1,Y1))
bonett.seier.test(p)