What are the similarities between the Chi-square test and McNemars test?
For McNemar , data are arranged in a contingency table with the same categories on each axis. So you have to know for each individual, e.g. Person 1 was in category A before and category B after, Person 2 was in category B before and category B after. You at least need to know the counts of subjects that switched from A to B, A to C, etc. If you don't have this information then you can't use McNemar. Overall, McNemar tests if people switched from category A to category B more than people switched from category B to category A, etc. If you want to see if there is a _correlation_ between the two, it is a totally different hypothesis. You would arrange the data in the same way as the McNemar test, but use a chi-square test. In this case you are testing if someone in category A before is likely to be in category A after.
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