> #6.6 CMH Analysis of Ordinal Trinary Example
> 
> #the data are coded here so "-"=1, "0"=2 and "+"=3
> x<-rbind(
+ c(2,1,2),
+ c(2,3,2),
+ c(2,1,2),
+ c(1,2,1),
+ c(1,2,1),
+ c(1,3,2),
+ c(1,3,2),
+ c(1,3,1))
> colnames(x)<-c("X","Y","Z")
> 
> #contingency tables used for CMH analysis
> xtoCMH(x)
, , Consumer = 1

   
    1 2 3
  X 0 1 0
  Y 1 0 0
  Z 0 1 0

, , Consumer = 2

   
    1 2 3
  X 0 1 0
  Y 0 0 1
  Z 0 1 0

, , Consumer = 3

   
    1 2 3
  X 0 1 0
  Y 1 0 0
  Z 0 1 0

, , Consumer = 4

   
    1 2 3
  X 1 0 0
  Y 0 1 0
  Z 1 0 0

, , Consumer = 5

   
    1 2 3
  X 1 0 0
  Y 0 1 0
  Z 1 0 0

, , Consumer = 6

   
    1 2 3
  X 1 0 0
  Y 0 0 1
  Z 0 1 0

, , Consumer = 7

   
    1 2 3
  X 1 0 0
  Y 0 0 1
  Z 0 1 0

, , Consumer = 8

   
    1 2 3
  X 1 0 0
  Y 0 0 1
  Z 1 0 0

> 
> #CMH analysis
> CMHanalysis(x)
                           Statistic df     pvalue
Extended Stuart                  9.0  4 0.06109948
Mean Score Differences           5.2  2 0.07427358
Non-Mean Score Differences       3.8  2 0.14956862
Correlation                      0.4  1 0.52708926
>