RWPNPBT

Performs a non-parametric bootstrap test using Rademacher wild bootstrap re-sampling.
This test compares all pairwise group means using a standardized distance metric,
making it robust to violations of normality and heteroscedasticity.

Implements three test procedures using bootstrap resampling techniques for assessing treatment effects in one-way ANOVA models with unequal variances (heteroscedasticity). It includes a parametric bootstrap likelihood ratio test (PB_LRT()), a pairwise parametric bootstrap mean test (PPBMT()), and a Rademacher wild pairwise non-parametric bootstrap test (RWPNPBT()). These methods provide robust alternatives to classical ANOVA and standard pairwise comparisons when the assumption of homogeneity of variances is violated.

Sagar Salvi

bootLRTpairwise

Bootstrap Hypothesis Tests for Treatment Effects in One-Way
ANOVA with Unequal Variances

Diya Somichan

Anjana Mondal

RWPNPBT function

<dl><dt>group_list</dt>
<dd>A list where each element is a numeric vector of raw observations for a group.</dd>
<dt>B</dt>
<dd>Number of bootstrap re-samples. Default is 100000.</dd>
<dt>alpha</dt>
<dd>Significance level for the hypothesis test. Default is 0.05.</dd></dl>

Arguments

Rademacher Wild Pairwise Non-Parametric Bootstrap Test (RWPNPBT) — RWPNPBT

<dl>

<dt>group_list</dt>
<dd>A list where each element is a numeric vector of raw observations for a group.</dd>


<dt>B</dt>
<dd>Number of bootstrap re-samples. Default is 100000.</dd>


<dt>alpha</dt>
<dd>Significance level for the hypothesis test. Default is 0.05.</dd>

</dl>

RWPNPBT: Rademacher Wild Pairwise Non-Parametric Bootstrap Test (RWPNPBT)

Description

Usage

Value

Arguments

Details

Examples