Thanks for your reply Chris Chapman! I didn’t know that LCA could estimate segments alongside utilities.
I’d like to apply the methods you described in this blog to a current project. My survey includes some additional questions besides the MaxDiff tasks, and I don’t want to stretch participants’ patience too much. I’m wondering if it’s feasible to show each item an average of only two times per respondent and still obtain informative individual-level results. Or do you think this would be a “bad” idea and that it’s better to avoid analyzing individual scores in this case?
The answer is probably, “It depends,” but if I’m not conducting a segmentation study and just want to identify whether some items seem particularly important to certain respondents, could the following principle apply?
“Our job is to help make decisions under uncertainty. We aim to take better bets. Sometimes it’s acceptable to show items only twice on average, if that’s the best we can reasonably do.”
Thanks Chris Chapman for this great blog article!
In your Quant UX book, you recommend using a higher number of tasks per participant to achieve precise individual-level estimates. However, in this blog, you used only 6 tasks for the MaxDiff analysis, which, according to your book, would primarily yield precise sample-level estimates.
I’m curious: How much of an impact does a relatively low number of tasks have on the precision of individual-level estimates?
Can you elaborate when I should definitely follow the textbook recommendation of 12-15 tasks (depending on the specific MaxDiff)? I would think that a segmentation study needs more accuracy then a simple analysis if there is an item that is highly important to some survey participants?!