NSM3 (version 1.18)

pDurSkiMa: Durbin, Skillings-Mack

Description

Function to compute the P-value for the observed Durbin, Skillings-Mack D statistic.

Usage

pDurSkiMa(x,b=NA,trt=NA,method=NA,n.mc=10000)

Value

Returns a list with "NSM3Ch7p" class containing the following components:

k

number of treatments in the data

n

number of blocks in the data

ss

number of treatments per block

pp

number of observations per treatment

lambda

number of times each pair of treatments occurs together within a block

obs.stat

the observed D statistic

p.val

upper tail P-value

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.

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: pDurSkiMa(x=matrix(c(1,2,3,4,5,6),ncol=2,byrow=T)) pDurSkiMa(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 7.6 Chemical Toxicity
table7.12<-matrix(nrow=7,ncol=7)
table7.12[1,c(1,2,4)]<-c(0.465,0.343,0.396)
table7.12[2,c(1,3,5)]<-c(0.602,0.873,0.634)
table7.12[3,c(3,4,7)]<-c(0.875,0.325,0.330)
table7.12[4,c(1,6,7)]<-c(0.423,0.987,0.426)
table7.12[5,c(2,3,6)]<-c(0.652,1.142,0.989)
table7.12[6,c(2,5,7)]<-c(0.536,0.409,0.309)
table7.12[7,c(4,5,6)]<-c(0.609,0.417,0.931)

pDurSkiMa(table7.12)

##or, equivalently:
x<-c(.465,.602,.423,.343,.652,.536,.873,.875,1.142,.396,.325,.609,.634,.409,.417,.987,.989,
.931,.330,.426,.309)
b<-c(1,2,4,1,5,6,2,3,5,1,3,7,2,6,7,4,5,7,3,4,6)
trt<-c(rep("A",3),rep("B",3),rep("C",3),rep("D",3),rep("E",3),rep("F",3),rep("g",3))

pDurSkiMa(x,b,trt)