# cJCK: Computes a critical value for the Jonckheere-Terpstra J... In NSM3: Functions and Datasets to Accompany Hollander, Wolfe, and Chicken - Nonparametric Statistical Methods, Third Edition

 cJCK R Documentation

## Computes a critical value for the Jonckheere-Terpstra J distribution.

### Description

This function computes the critical value for the Jonckheere-Terpstra J distribution at (or typically in the "Exact" case, close to) the given alpha level. The function takes advantage of Harding's (1984) algorithm to quickly generate the distribution.

### Usage

cJCK(alpha, n, method=NA, n.mc=10000)

### Arguments

 alpha A numeric value between 0 and 1. n A vector of numeric values indicating the size of each of the k data groups. method Either "Exact" or "Asymptotic", indicating the desired distribution. When method=NA, if sum(n)<=200, the "Exact" method will be used to compute the J distribution. Otherwise, the "Asymptotic" method will be used. n.mc Not used. Only included for standardization with other critical value procedures in the NSM3 package.

### Value

Returns a list with "NSM3Ch6c" class containing the following components:

 n number of observations in the k data groups cutoff.U upper tail cutoff at or below user-specified alpha true.alpha.U true alpha level corresponding to cutoff.U (if method="Exact")

Grant Schneider

### References

Harding, E. F. "An efficient, minimal-storage procedure for calculating the Mann-Whitney U, generalized U and similar distributions." Applied statistics (1984): 1-6.

### Examples

##Hollander-Wolfe-Chicken Example 6.2 Motivational Effect of Knowledge of Performance
cJCK(.0490, c(6,6,6),"Exact")
cJCK(.0490, c(6,6,6),"Monte Carlo")
cJCK(.0231, c(6,6,6),"Exact")

NSM3 documentation built on Sept. 8, 2023, 5:52 p.m.