There is a friedman.test() function. Any reason you want to do it by hand?
If so, you can do:
#Simulated data matrix
x<-matrix(rnorm(9),3,3,byrow=T)
x
#Rank matrix
r<-matrix(rank(x),dim(x))
HTH,
Daniel
JohnnyJames wrote:
>
> My data looks like this:
> (treatments)
> T1 T2 T3
> DK 8 5 3
>
> JP 5 4 1
>
> AS 9 7 4
>
> MK 8 4 4
>
> DK, JP, AS, and MK are 4 different people (blocks) I am using.
>
> This is my code so far:
>
>> treat<-c("J","J","J","J","U","U","U","U","H","H", "H", "H")
>
>> y<-c(8,5,3,5,4,1,9,7,4,8,4,4)
>
>> block<-c("DK","JP","AS","MK","DK","JP","AS","MK","DK","JP","AS","MK")
>
>> ranks<-matrix(NA,nrow=4,ncol=3)
>
>> for (i in 1:4) ranks[i,]<-??????????????????
>
> I know that once I can get the ranks stored I can do a command like below.
>
>> summary(aov(as.vector(ranks)~factor(treat)+factor(block)))
>
> Can someone help me store the data as ranks?
>
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