# Has anyone used the Marascuilo procedure for comparing multiple proportions?

The Marascuilo procedure as described here seems to be a test that addresses the issue of multiple comparisons for proportions when you want to test which specific proportions are different from each other after rejecting the null in an overall chi-square test.

However, I am not very familiar with this test. So, my questions:

1. What nuances (if any) should I worry about when using this test?

2. I know of at least two other approaches (see below) to address the same issue. Which test is the 'better' approach?:

• Perhaps this discussion is relevant as -- it isn't often used because it is very conservative (much like Scheffe's Method)? – M. Tibbits Oct 12 '10 at 19:06
• Surely you mean "after rejecting the null" not "after failing to reject the null"? And it seems there's only one L in 'Marascuilo' (NIST's error, not yours): Leonard A. Marascuilo. Large-sample multiple comparisons. Psychological Bulletin, 1966; 65(5): 280-290. dx.doi.org/10.1037/h0023189. – onestop Oct 12 '10 at 21:58

In R, there is a function pairwise.prop.test() which allows any correction for multiple comparisons (single-step or step-down FWER methods or FDR-based), but it is quit what you already suggested (although Bonferroni is by far too conservative, but still very used in practice). A resampling approach, using permutation, might be interesting too. The coin R package provides a well-established testing framework in this respect, see §5 of Implementing a Class of Permutation Tests: The coin Package, but I never had to deal with permutation tests on categorical data in a post-hoc way.