# Post hoc chi-square test

I am looking at a $\chi^2$ (crosstabs) test looking at interactions between types of dyads in an animal group. My categories are Male-Male, Male-Female, and Female-Female dyads in the rows and "Were Seen to Interact" and "Were Never Seen to Interact".
The matrix looks something like:

21   7
85   19
77   1


There is a very significant p value. My question is, when running the post hoc tests, is it appropriate to compare each category to the sum of the other two (i.e. Male-Male, vs Male-Female+Female-Female) when looking for which category is driving the difference, or should I compare the categories to each other (Male-Male vs Male-Female, then Male-Male vs Female-Female)?

I'm looking for an answer to the question of whether one of the types of dyads are more likely to fail to interact. I think the statement "There are more Males-Female dyads that were never seen to interact than would be expected by chance" would be easier to comprehend than if I had to write out the comparisons of the three pairs. I just don't know if it's allowable.

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A related question I asked a while ago: stats.stackexchange.com/questions/961/… –  nico Sep 5 '11 at 19:02