We are developing a questionnaire for evaluation of burden of disease after certain medical conditions. The questions are developed partly from semistructured interviews. My statistician argues for using both exploratory and confirmatory FA for item reduction etc. The questionnaire is large; it contains questions in what I think will turn out to be 10-13 domains, each containing 6-30 items.
I'm curious as to how to handle the fact that we're using a control group. We have a group of 2000 patients and 500 in a health control group. As I understand FA will be an excellent way of extracting factors, deciding of number of factors to retain and performing rotation. We would proably use maximum likelihood, then parallel analysis followed by a proper rotation.
In my (novice) understanding of FA, this would be a typical way of reducing a questionnaire in for example psychological tests, where one could discuss latent variables, factors etc.
- Are these methods really useful when it comes to item-reduction in questionnaires asking for symptoms and comparing to a healthy control group?
- Would one first perform the FA on answers from the un-healthy group to see what questions "falls out" per se and then compare those specific questions with the healthy control group or would one instead perform the same analysis on the entire study population at once?
- Is FA, at least exploratory, entirely wrong in this context? We have already created empirical domains e.g. "Sleep" which contains questions like "How often do you wake up at night?" but other questions like "Have you had negative thoughts about your body" could fit within both the sexual domain as well as the physical and the psychological. In my simple mind the first example would not need an analysis to find out under which domain it belongs, but the second example would. On the other hand, maybe exploratory FA would be an ojective way of finding out whether the domains are "correct" or not?
Please downvote if these questions not really fit the rules on CV, so that I can delete it. Otherwise, please guide me through these steps. My background is, rather obviously, not in statistics.