PairedData (version 0.5)

pitman.morgan.test: Pitman-Morgan test of variances for paired samples

Description

Classical test of variance for paired samples based on the bivariate normal distribution

Usage

pitman.morgan.test(x, y = NULL, alternative = c("two.sided", "less", "greater"),
         omega = 1, conf.level = 0.95)

Arguments

x

First sample

y

Second sample

alternative

Alternative hypothesis

omega

A priori ratio of variances

conf.level

Confidence level

Value

• A list with class "htest" containing the following components:
• statistic
  The value of the F-statistic
• parameter
  The degrees of freedom for the F-statistic
• p.value
  The p-value for the test
• conf.int
  A confidence interval for the ratio of variances appropriate to the specified alternative hypothesis
• estimate
  The estimated variances
• null.value
  The specified hypothesized value of the ratio of variances
• 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

• W. A. Morgan. A test for the significance of the difference between two variances in a sample from a normal bivariate distribution. Biometrika, 31, 13-19, 1939.
• E.J.G. Pitman. A note on normal correlation. Biometrika, 31, 9-12, 1939.

See Also

var.test, bonett.seier.test, grambsch.test

Examples

z<-rnorm(20)
x<-rnorm(20)+z
y<-(rnorm(20)+z)*2
pitman.morgan.test(x,y)