wgf.test {onewaytests}

Weerahandi's Generalized F Test

Description

wgf.test performs Weerahandi's generalized F test.

Usage

wgf.test(formula, data, N = 10^5, alpha = 0.05, na.rm = TRUE, verbose = TRUE)

Arguments

formula

a formula of the form lhs ~ rhs where lhs gives the sample values and rhs the corresponding groups.

data

a tibble or data frame containing the variables in formula.

N

the number of bootstrap samples. Default is set to 10^5.

alpha

the level of significance to assess the statistical difference. Default is set to alpha = 0.05.

na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

verbose

a logical for printing output to R console.

Value

A list with class "owt" containing the following components:

p.value

the p-value of Weerahandi's generalized F test.

alpha

the level of significance to assess the statistical difference.

method

the character string "Weerahandi's Generalized F Test".

data

a data frame containing the variables in which NA values (if exist) are removed.

formula

a formula of the form lhs ~ rhs where lhs gives the sample values and rhs the corresponding groups.

N

the number of bootstrap samples.

Note

The user can contact the author of this code, Sam Weerahandi, for additional information about the method and the code.

Author(s)

Sam Weerahandi

References

Weerahandi, S. (1995). ANOVA under Unequal Error Variances. Biometrics, 589-599.

Examples

library(onewaytests)


wgf.test(Sepal.Length ~ Species, data = iris)

out <- wgf.test(Sepal.Length ~ Species, data = iris)
paircomp(out)