[R] Estimating choice models at the individual level

[Chris Chapman]

The "bayesm" package does HB models for discrete choice. In practice, a hurdle is likely to be translating your data (if it's fielded in Sawtooth Software) to the correct format for bayesm (which uses a list format instead of a matrix, and difference coding instead of dummy coding).

(BTW, note another R list: R-SIG-DCM, which you might consider joining if you're not already a member. https://stat.ethz.ch/mailman/listinfo/r-sig-dcm )

Good luck,

-- Chris

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Data Analytics Corp.
Sent: Tuesday, June 21, 2011 7:45 AM
To: r-help at r-project.org
Subject: [R] Estimating choice models at the individual level

Hi,

I have a discrete choice model to estimate for a client that I originally planned to estimate as an aggregate model using a clogit routine.  Now the client is asking for results for many segments of the respondents which would mean, if I stayed with my original plan, I would have to estimate a large number of models.  I could certainly do this, but I'm thinking that it would be better to estimate a Hierarchical Bayes model to get coefficients for each individual respondent.  This way, I could pull out the people I need for a particular segment and use just those coefficients.  Sawtooth's program for MaxDiff can do this.  
Is there any R package to do an HB estimation for a discrete choice
(logit) model?

Thanks,

Walt

________________________

Walter R. Paczkowski, Ph.D.
Data Analytics Corp.
44 Hamilton Lane
Plainsboro, NJ 08536
________________________
(V) 609-936-8999
(F) 609-936-3733
walt at dataanalyticscorp.com
www.dataanalyticscorp.com

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