PairedData (version 0.9.1)

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

Description

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

Usage

pitman.morgan.test(x, ...)

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

## S3 method for class 'paired':
pitman.morgan.test(x, ...)

Arguments

x

first sample or an object of class paired.

y

second sample.

alternative

alternative hypothesis.

omega

a priori ratio of variances.

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 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

data(HORSEbegin)
pitman.morgan.test(HORSEbegin$Actual,HORSEbegin$Imaginary)

p<-with(HORSEbegin,paired(Actual,Imaginary))
pitman.morgan.test(p)