# Conjoint Analysis - Incorporating individual-specific intercept

We are new here, and have recently gotten a question that we have very much been struggling to answer. It is concerning a question regarding a conjoint analysis in which we have to incorporate an individual-specific intercept. We are working with the a regression model that includes:

• 15 Consumers (subjects)
• 22 Profiles 
• 1 - 5 attributes
• amount of Levels varying from 2 levels to 3 levels

We already have all dummies needed to conduct a general conjoint analysis in SPSS. This question however is as follows:

while consumers’ preferences over different attributes and levels are more or less the same, they do have different baseline level of utility (constant terms). As a consequence, to derive more accurate estimation of consumers’ part-worth values, researchers need to make the intercept individual-specific (but the part-worth values are the same across consumers). In your analysis, try to think of a way to incorporate individual-specific intercept in the regression.

We have tried many different approaches but haven't fully figures out how to solve this problem. Can anybody maybe give us some tips? We highly appreciate it!

• Conjoint analysis (and the basic one, full-profile conjoint in available SPSS) is by default done separately for each individual. It is ANOVA modeling performed for each of $n$ respondents. You thus get $n$ equations with their utilities and intercepts. You can request also to output omnibus model which combines all respondents. Nov 21, 2015 at 16:41
• You seem to want to try an in-between approach: omnibus utility terms but individual intercept levels. One would ask why you think this is warranted. Why, really, individual reactions should be identical on one model's parameter and differ on the other parameter? Well, if you have reasons to insist - you may do such analysis, but I doubt much that it is possible via the Conjoint command. That might be possible, I suppose, via mixed models or GEE; right now I can't recommend you a specific way, it has to be overhauled. Nov 21, 2015 at 16:47
• Apart from the Hierarchical Bayes logit model, one may also use the mixed logit model under the classical approach. The mlogit package or the gmnl package will do the trick. Nov 30, 2016 at 16:35