bootLRTpairwise (version 0.2.0)

PPBMT: Pairwise Parametric Bootstrap Mean Test (PPBMT)

Description

Performs a parametric bootstrap test to compare all pairwise group means under heteroscedasticity, assuming normality of the data.

Usage

PPBMT(means, vars, ns, B = 1000, alpha = 0.05)

Value

A list of class "PPBMT" containing:

test_statistic

Observed value of the test statistic.

critical_value

Bootstrap-based critical value.

decision

Conclusion of the hypothesis test.

Arguments

means

A numeric vector containing the sample means for each group.

vars

A numeric vector containing the sample variances for each group.

ns

An integer vector indicating the sample sizes of each group.

B

Number of bootstrap re-samples. Default is 1000.

alpha

Significance level for the hypothesis test. Default is 0.05.

Examples

# Example with 3 groups
set.seed(123)
g1 <- rnorm(20, mean = 5, sd = 1.5)
g2 <- rnorm(25, mean = 6.5, sd = 2)
g3 <- rnorm(22, mean = 7.2, sd = 2.5)

means <- c(mean(g1), mean(g2), mean(g3))
vars <- c(var(g1), var(g2), var(g3))
ns <- c(length(g1), length(g2), length(g3))

result <- PPBMT(means, vars, ns, B = 1000, alpha = 0.05)
print(result)