However, it is also possible to test them as $(b-c)^2/(b+c)$. The short version is that McNemar's test is actually a binomial test of whether the two off-diagonal cell counts (often denoted cells b & c) diverge from an expected null ratio of $1$ to $1$. It may help you to read my answers to What is the difference between McNemar's test and the chi-squared test, and how do you know when to use each? here, and here. I hope someone has some insight on this.Thanks! On the other hand, why not just report the Chi-Square and the accompanying p-value of the second method? The first p-value is based on the binomial distribution so I guess reporting the Chi-Square does not make sense. However, I am wondering if I should also report the Chi-Square value. In the end the most important thing is that there is a significant change from before to after the treatment. However, when I run the McNemar test using the nonparametrics tests -> related samples function, the Chi-Square is also reported, 58.061, AsympSig. It also notes that the binomial distribution is used to determine this. When I run the McNemar test using the cross-tabs function in SPSS it does not report a test-value, only the Exact Sig (2-sided), which in my case is. I have performed a McNemar test for paired binomial variables in SPSS to see if the success rate(score 1) differs between the two conditions (the two variables: the before and after treatment variables).