I am currently writing my Masters Thesis and was luckily enough to get to know Sawtooth software for my preference problem.
I set up a survey where participants had to answer 18 BestWorst questions. The attributes list contains 30 attributes, while I choosed to show every item 3x. The question design is random (every participant received a different question sample)
For now, I manually did counting analysis and rationale scale analysis to rank my items.
I am planning to integrate the Sawtooth "TURF" analysis to verify my results (in case of population reach for the "best-scaled" items)
Now I am wondering on how to test statistical difference between those items, since I have no classical categorization questions (atleast not enough as I have only 90 respondents).
I read alot about the logit-model or HB-testing, but honestly I don't understand these testing mechanisms for my case.
My thoughts were to apply simple t-tests for the rescaled scores delivered by the MaxDiff-analyzer. I could sup-sample my data into those participants with a rescaled-score of 100 and those with sum_rescaled_scores ><100. What do you think about this?
Gladly for all your effort, I remain with best wishes from Germany.
Thanks in advance, Tobias