I conducted a MaxDiff and now want to look deeper into various sub-groups within my sample. By comparing various methods I came down to 4 options:
1. Running HB analysis on the whole sample, split the data file afterwards into the sub-groups and use the averages for each sub-group. However, I realized that this method would calculate the results "borrowing" information from the whole population, so larger sub-groups would dominate and influence the results for smaller groups.
2. Running HB analysis on whole sample but adapt the prior variance in the advanced settings in order to shift more weight to the individual responses and away from the whole population. --> Which variance would be suitable in that case, as the value can be chosen from 0.1 to 100?
3. Enter co-variates for the various sub-groups before running the HB analysis. However, I learned that this slows down the process and doesn't necessarily enhance the results.
4. Split the file manually and upload the sub-group data separately to run separate HB analyses on each file. I think that worked in Sawtooth version 6, but I didn't find a way to do it in version 8, as this version seems to pull the data for HB analysis directly from the online database.
Does anyone have an idea with which option the data quality would be best or whether there are other possibilities?
Thanks a lot in advance!