There are two ways I’m thinking about doing the data analysis: In the first analysis, each patient is a data point. So there are 100 dichotomous data points (SA or MA) pre-seminar and 100 dichotomous post-seminar. If we do this approach, I think the data do not meet the independence requirement of a chi squared test (the same set of nurses are involved pre/post). So I think it would be a McNemar’s Test. We would match Nurse 1/Case 1/Pre-seminar with Nurse 1/Case 1/Post-seminar then Nurse 1/Case 2/Pre with Nurse 1/Case 2/Post, etc. Would this be an acceptable use of McNemar’s Test? I know it’s not the typical use of McNemar’s because there are multiple observations from each nurse in the pre and post periods.

In the second approach, each nurse is the data point. We record for each of the 25 nurses the proportion of SA trials pre- and post-seminar. Because the student believes most of the proportions will be 0 or 1 (the same nurse typically does the same thing) or close to that (like 0.2 or 0.8), I was thinking of dichotomizing the variable. My understanding is that with 25 nurses, that is not sufficient to do a McNemar’s Test. We would look at the number of instances where nurses switched from MA in the Pre to SA in the Post compared to the reverse switch and do a binomial test. Would dichotomizing the proportions and doing a binomial test be OK?

I am thinking we could report both of the tests above. Would it be acceptable to do this? Even if yes, are there better ways to analyze the data?