# Interpreting HB conjoint results

Hi,

We are trying to interpret the results of our Hierarchial Bayes Conjoint study.

- What do these utilities imply ? We want to look at interactions between some variables the sum of the utilities is 0, so it cannot be just avarages?

- How can you calculate/estimate your p values of each level of a variable?

- You get utilities for each level of a variable, but how can you know something about just one variable ?

Some questions that we are currently having, but it would be good to have a chat with someone who already intrepreted the results of HB previously.

+1 vote
Hello.

You can find a basic introduction to utilities here:  https://www.sawtoothsoftware.com/support/technical-papers/general-conjoint-analysis/the-basics-of-interpreting-conjoint-utilities.

I do not understand this sentence, so please clarify:  'We want to look at interactions between some variables the sum of the utilities is 0, so it cannot be just avarages?"

In terms of getting a p-value for each level of each attribute, the easiest thing would be to estimate the utilities with a logit model and then look at the t statistics.  If you want to keep with HB estimation, you could go into the draws file and for each attribute level, count the proportion of times the utility was above (or below) zero.  That proportion would be analogous to a p-value for the utility of that level being positive (or negative, respectively).
answered Mar 31, 2014 by Platinum (62,700 points)
Hi,

Thanks for this information.

We are having 4 factors with each factor having 3 levels. (Macro - Micro1 Micro2 Micro3). We want to determine if the effect of each level of all micro-variables is the same in each level of the macro variable.

And what would a significant p value imply? That there is a difference within each factor between the levels?
Is this like a regression or what kind of analysis is this actually performing when you just do hb in sawtooth v8?

Thanks