cJCK {NSM3}

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")

Author(s)

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")