When we run the HB estimation on MaxDiff data, we get three sets of scores:
1) Zero centered raw scores
2 Zero centered interval scores
3) Probability based Rescaled scores
For our studies, we use the Zero centered raw scores to calculate the Share of Preference % using the exp(i) / sum of all exp(ij) formula.
We had two questions about these:
1) What is the difference between Zero centered raw vs. Zero centered interval scores?
2) If we REALLY had to pick one between the Share of Pref. % and Probability based Rescaled scores (which also sum to 100), which one would that be and why?
It seems like both the Share of Pref. % and Probability based rescaled scores are calculated based on the same raw scores, but they do give different outputs a lot of times (both in terms of ranking of attributes as well as the percentage value). We want to know which model is more robust and recommended.
Thank you in advance for your valuable time, please let me know if you have any clarifying questions.