I am interested in conducting a sparse max diff with 200 items. My client has strong preference for showing at most 5 items per max diff question and having at most 12 max diff questions per respondent.
With sparse max diff and 200 items, showing each item once will require 40 max diff questions per respondent [(200/5) * 1 = 40]. I have used sparse max diff in the past and most sparse I've ever used was showing each item once per respondent.
To meet the client's request, however, each item would be shown 0.3 times [(200/5) * 0.3 = 12].
My question is, in sparse max diff when you need to show each item less than once per respondent, how sparse can you get? That is, is showing each item 0.3 times per respondent OK, 0.25 times per respondent OK, or have practitioners found that you should not go lower than (say) 0.5 times per respondent?
For analysis I will need to run HB estimation in Lighthouse Studio to obtain respondent-level max diff scores (as is done with regular non-sparse max diff designs). So my question is being asked (and needs an answer) in terms of recommendations for this type of analysis (versus aggregate logit). That is, How sparse can you go and still be able to estimate HB scores in Lighthouse Studio?