The question of the week is:

What statistical test do I use when I have pre/post reflective questions.

First, what is a reflective question?

Ask says: “A reflective question is a question that requires an individual to think about their knowledge or information, before giving a response. A reflective question is mostly used to gain knowledge about an individual’s personal life.”

I assume (and we have talked about assumptions before assume) that these items were scaled to some hierarchy, like a lot to a little, and a number assigned to each.  Since the questions are pre/post, they are “matched” and can be compared using a comparison test of dependence, like a t-test or a Wilcoxon.  However, if the questions are truly nominal (i.e., “know” and “not know”) and in response to some prompt and DO NOT have a keyed response (like specific knowledge questions),  then even though the same person answered the pre questions and the post questions there really isn’t established dependence.

If the data are nominal, then using a chi-square test would be the best approach because it will tell you if there is a difference from what was expected and what was actually observed (responded).  On a pre/post reflective question, one would expect that they respondents would “know” some information before the intervention, say 50-50 and after the intervention, that difference would shift to say 80 “know” to 20 “not know”.  A chi-square test would give you a statistic of probability that that distribution on the post occurred by chance.  SPSS will run this test; find it under the non-parametric tests.

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