# pDurSkiMa: Durbin, Skillings-Mack In NSM3: Functions and Datasets to Accompany Hollander, Wolfe, and Chicken - Nonparametric Statistical Methods, Third Edition

## Description

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

## Usage

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

## 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.

## 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))`

## 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

Grant Schneider

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```##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) ```

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