On Mon, May 04 2009, Linda Mortensen wrote: > Dear R-language experts, > > I'm trying to run a logistic regression on ordered multinomial data. - > The dependent variable is number of correct items with accuracy > ranging from 0 to 5. I want to use a mixed-effects model, but am > unsure about how to use this model to fit multinomial data. Can you > help?
Hi Linda-- I've posted my response to this question at http://hlplab.wordpress.com/2009/05/07/multinomial-random-effects-models-in-r/. While I've recently had some success using MCMCglmm for unordered multinomial data, I have no experience with analyzing ordered categorical data in R. The relevant kinds of models are proportional odds regression (the polr function from the MASS package, for example) and multinomial probit regression, but I don't know which R packages (if any) allow random effects in those frameworks. The post linked above includes a list of candidate packages that you might want to check out. At least one, mprobit, seems to allow structured variance based on a cluster term. Thanks, /au -- Austin Frank http://aufrank.net GPG Public Key (D7398C2F): http://aufrank.net/personal.asc
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