Hello all,
I wish to perform a mcnemar test for a 3 by 3 matrix.
By running the slandered R command I am getting a result but I am not sure I
am getting the correct one.
Here is an example code:
(tt <- as.table(t(matrix(c(1,4,1 ,
0,5,5,
3,1,5), ncol = 3))))
mcnemar.test(tt, correct=T)
#And I get:
McNemar's Chi-squared test
data: tt
McNemar's chi-squared = 7.6667, df = 3, p-value = *0.05343*
Now I was wondering if the test I just performed is the correct one.
>From looking at the Wikipedia article on mcnemar (
http://en.wikipedia.org/wiki/McNemar's_test), it is said that:
"The Stuart-Maxwell
test<http://ourworld.compuserve.com/homepages/jsuebersax/mcnemar.htm>
is
different generalization of the McNemar test, used for testing marginal
homogeneity in a square table with more than two rows/columns"
>From searching for a Stuart-Maxwell
test<http://ourworld.compuserve.com/homepages/jsuebersax/mcnemar.htm>
in
google, I found an algorithm here:
http://www.m-hikari.com/ams/ams-password-2009/ams-password9-12-2009/abbasiAMS9-12-2009.pdf
>From running this algorithm I am getting a different P value, here is the
(somewhat ugly) code I produced for this:
get.d <- function(xx)
{
length1 <- dim(xx)[1]
ret1 <- margin.table(xx,1) - margin.table(xx,2)
return(ret1)
}
get.s <- function(xx)
{
the.s <- xx
for( i in 1:dim(xx)[1])
{
for(j in 1:dim(xx)[2])
{
if(i == j)
{
the.s[i,j] <- margin.table(xx,1)[i] + margin.table(xx,2)[i] -
2*xx[i,i]
} else {
the.s[i,j] <- -(xx[i,j] + xx[j,i])
}
}
}
return(the.s)
}
chi.statistic <- t(get.d(tt)[-3]) %*% solve(get.s(tt)[-3,-3]) %*%
get.d(tt)[-3]
paste("the P value:", pchisq(chi.statistic, 2))
#and the result was:
"the P value: 0.268384371053358"
So to summarize my questions:
1) can I use "mcnemar.test" for 3*3 (or more) tables ?
2) if so, what test is being performed (
Stuart-Maxwell<http://ourworld.compuserve.com/homepages/jsuebersax/mcnemar.htm>)
?
3) Do you have a recommended link to an explanation of the algorithm
employed?
Thanks,
Tal
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