Hierarchical multinomial logit with R/JAGS

Question

I am working on a small project where I have to do a Choice Based Conjoint (CBC) analysis. In order to get the part-worths for the different consumers I need to estimate a hierarchical multinomial model. Does anyone know how to do this in R/JAGS, and how to save the estimated coefficients for each consumer in a .csv file?

score 4 · Accepted Answer · answered Jul 02 '12 at 06:12

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After a bit og Googling I found the following package which does the trick: http://cran.r-project.org/web/packages/ChoiceModelR/index.html

answered Jul 02 '12 at 06:12

Thomas Jensen

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score 1 · Answer 2 · answered Jun 28 '12 at 14:00

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MCMCpack has implemented a multinomial logit which will probably be considerably faster than one you've implemented yourself in JAGS, presuming that it meets your needs.

MCMCmnl(formula, baseline=NULL, data=NULL,
        burnin = 1000, mcmc = 10000, thin = 1,
        mcmc.method = c("IndMH", "RWM", "slice"), tune = 1, tdf=6,
        verbose = 0, seed = NA, beta.start = NA, b0 = 0, B0 = 0, ...)

More documentation: http://mcmcpack.wustl.edu/

answered Jun 28 '12 at 14:00

Zach

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Hi Zach, thanks for the reference, but MCMCpack does not seem to offer any hierarchical version of multinomial logit. – Thomas Jensen Jun 29 '12 at 06:43
Ah indeed, I conveniently read over "hierarchical" – Zach Jun 29 '12 at 17:37

Hierarchical multinomial logit with R/JAGS

2 Answers2