Performing a non parametric Friedman Test
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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