# cNWWM: Computes a critical value for the Nemenyi, Wilcoxon-Wilcox,... In NSM3: Functions and Datasets to Accompany Hollander, Wolfe, and Chicken - Nonparametric Statistical Methods, Third Edition

## Description

This function computes the critical value for the Nemenyi, Wilcoxon-Wilcox, Miller R* distribution at (or typically in the "Exact" and "Monte Carlo" cases, close to) the given alpha level.

## Usage

 `1` ```cNWWM(alpha, k, n, method=NA, n.mc=10000) ```

## Arguments

 `alpha` A numeric value between 0 and 1. `k` A numeric value indicating the number of treatments. `n` A numeric value indicating the number of blocks. `method` Either "Exact", "Monte Carlo" or "Asymptotic", indicating the desired distribution. When method=NA, "Exact" will be used if the number of permutations is 10,000 or less. Otherwise, "Monte Carlo" will be used. `n.mc` If method="Monte Carlo", the number of Monte Carlo samples used to estimate the distribution. Otherwise, not used.

## Value

Returns a list with "NSM3Ch7c" class containing the following components:

 `k` number of treatments `n` number of blocks `cutoff.U` upper tail cutoff at or below user-specified alpha `true.alpha.U` true alpha level corresponding to cutoff.U (if method="Exact" or "Monte Carlo")

Grant Schneider

## Examples

 ```1 2 3 4 5 6``` ```##Hollander-Wolfe-Chicken Example 7.4 Stuttering Adaptation #cNWWM(.0492, 3, 18, "Monte Carlo") cNWWM(.0492, 3, 18, method="Monte Carlo",n.mc=2500) ##Comment 7.35 cNWWM(.0093, 3, 3, "Exact") #cNWWM(.0093, 3, 3, "Monte Carlo") ```

NSM3 documentation built on April 6, 2021, 5:05 p.m.