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I found similar threads on the forum, but none seems to apply to my case, so I decided to post the question.

My response variable is an ordered 1-4 likert scale. I asked three subjects to rate the linguistic quality of sentences pre and post a linguistic revision process carried out on the sentences. I decided that the best way forward is analysing the post scores, having pre scores as a predictor in ordinal regression.

Since I have three versions of the scale (3 subjects), if I use mixed-effects analysis with a random effect of subject, I'd end up having the same sentence with different pre scores in the data (from different subjects), which does not seem coherent.

Would it be OK to use averages (both for the dependent variable and for the pre score)? I would still treat the dependent variable as ordinal (now with 9 levels), instead of being 1-4, it'd have intermediate categories, say 1, 1.3, 1.6, 2...

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    $\begingroup$ To be able to be averaging in the first place, you have already decided to treat your variables as interval scale. It doesn't become less interval-scale after averaging. $\endgroup$
    – Glen_b
    Jun 25 '14 at 11:54
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My first thought would be to use a mixed model. Why, in your 3rd paragraph, do you say this does not seem coherent? You do not, as far as I can see, have three versions of the scale.

Using the averages does not make much sense to me, whether with ordinal regression or anything else. By doing this you are throwing away lots of information. Such an analysis will have much less power than other tests.

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  • $\begingroup$ For some reason it just didn't seem right that the same sentences would have different pre scores in the data, but you're right - these aren't 3 versions, but 3 sets of answers using the same scale. I'll proceed with a mixed model. Thanks for this! $\endgroup$ Jun 25 '14 at 10:48

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