NSM3 (version 1.18)

pWNMT: Wilcoxon, Nemenyi, McDonald-Thompson

Description

Function to compute the P-value for the observed Wilcoxon, Nemenyi, McDonald-Thompson R statistic.

Usage

pWNMT(x,b=NA,trt=NA,method=NA, n.mc=10000, standardized=FALSE)

Value

Returns a list with "NSM3Ch7MCp" class containing the following components:

k

number of treatments

n

number of blocks

obs.stat

the observed R* statistic for each of the k*(k-1)/2 comparisons

p.val

upper tail P-value corresponding to each observed R statistic

Arguments

x

Either a matrix or a vector containing the data.

b

If x is a vector, b is a required vector of block labels. Otherwise, not used.

trt

If x is a vector, trt is a required vector of treatment labels. Otherwise, not used.

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.

standardized

If TRUE, divide the observed statistic by (nk(k+1)/12)^0.5 before returning.

Author

Grant Schneider

Details

The data entry is intended to be flexible, so that the data can be entered in either of two ways. The following are equivalent: pWNMT(x=matrix(c(1,2,3,4,5,6),ncol=2,byrow=T)) pWNMT(x=c(1,2,3,4,5,6),b=c(1,1,2,2,3,3),trt=c(1,2,1,2,1,2))

Examples

##Hollander-Wolfe-Chicken Example 7.3 Rounding First Base
RoundingTimes<-matrix(c(5.40, 5.50, 5.55, 5.85, 5.70, 5.75, 5.20, 5.60, 5.50, 5.55, 5.50, 5.40,
5.90, 5.85, 5.70, 5.45, 5.55, 5.60, 5.40, 5.40, 5.35, 5.45, 5.50, 5.35, 5.25, 5.15, 5.00, 5.85,
5.80, 5.70, 5.25, 5.20, 5.10, 5.65, 5.55, 5.45, 5.60, 5.35, 5.45, 5.05, 5.00, 4.95, 5.50, 5.50,
5.40, 5.45, 5.55, 5.50, 5.55, 5.55, 5.35, 5.45, 5.50, 5.55, 5.50, 5.45, 5.25, 5.65, 5.60, 5.40,
5.70, 5.65, 5.55, 6.30, 6.30, 6.25),nrow = 22,byrow = TRUE,dimnames = list(1 : 22,
c("Round Out", "Narrow Angle", "Wide Angle")))

pWNMT(RoundingTimes,n.mc=2500)