Simulating contingency table (Basic question, help please)

I'd like to carry out a Monte Carlo simulation test where given data is a
contingency table. I think this is something to do with using rmultinonom(),
but I'm not sure how to code this, to simulate contingency tables. Could
anyone please help with how to use R to simulate contingency tables like
this?


Let m be your matrix (contingency table).

Do something like:

> p <- (rowSums(m)%o%colSums(m))/(sum(m)^2)
> X <- rmultinom(2000,sum(m),p)

and then

> simstat <- apply(X,2,function(x,k){chisq.test(matrix(x,nrow=k))$statistic},k=nrow(m))

will give you simulated chi-squared statistics.

If you want some other statistic then obviously you need to modify the function which is applied to the columns of X.

Note that the simulation is done under the usual contingency table null hypothesis of independence or
homogeneity.  If you have something else in mind you'll need to modify accordingly.

    cheers,

         Rolf Turner
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