onewaytests (version 3.1)

agp.test: Alvandi's Generalized P-Value

Description

agp.test performs Alvandi's generalized p-value. This test assumes normality within each group and provides an alternative to one-way ANOVA when variances are unequal. The p-value is obtained by comparing the observed Cochran's test statistic with the reference distribution calculated using Monte Carlo simulation.

Usage

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

Value

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

p.value

the Alvandi's generalized p-value.

alpha

the level of significance to assess the statistical difference.

method

the character string "Alvandi's Generalized P-Value".

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.

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.

Author

Merve Kasikci

References

Sadooghi-Alvandi, S.M., Jafari, A.A., Mardani-Fard, H.A. (2012). One-Way ANOVA with Unequal Variances. Communications in Statistics-Theory and Methods, 41:22, 4200-4221.

Examples

library(onewaytests)

# \donttest{
agp.test(Sepal.Length ~ Species, data = iris)

out <- agp.test(Sepal.Length ~ Species, data = iris, verbose = FALSE)
summary(out)
paircomp(out)
# }