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Our World Statistics Day conversations have been a great reminder of how much statistics can inform our lives. Do you have an example of how statistics has made a difference in your life? Share your story with the Community!
Nov 26, 2019 6:00 AM
| Last Modified: Nov 26, 2019 6:31 AM(597 views)
I am analyzing different mixed logit models on my data from a discrete choice experiment. Therefore, I use the 'Hierarchical Bayes' estimation procedure under 'Consumer Research'. However, if I select 'save utility formula', the parameters estimates that are saved are not the same as the calculated posterior means of my model. So, what does the saved parameter estimates represent then?
I provided the saved parameter estimates in the first image in attachment and the bayesian posterior means in the second image.