[R] Models for Discrete Choice in R

[Emmanuel Charpentier]

Le dimanche 08 novembre 2009 à 19:05 -0600, Frank E Harrell Jr a écrit :
> Emmanuel Charpentier wrote:
> > Le dimanche 08 novembre 2009 à 17:07 -0200, Iuri Gavronski a écrit :
> >> Hi,
> >>
> >> I would like to fit Logit models for ordered data, such as those
> >> suggested by Greene (2003), p. 736.
> >>
> >> Does anyone suggests any package in R for that?
> > 
> > look up the polr function in package MASS (and read the relevant pages
> > in V&R4 and some quoted references...) or the slightly more
> > sophisticated (larger range of models) lrm function in F. Harrell's
> > Design (now rms) packge (but be aware that Design is a huge beast witch
> > carries its own "computing universe", based on (strong) Harrell's view
> > of what a regression analysis should be : reading his book is, IMHO,
> > necessary to understand his choices and agree (or disgree) with them).
> > 
> > If you have a multilevel model (a. k. a. one "random effect" grouping),
> > the "repolr" packge aims at that, but I've been unable to use it
> > recently (numerical exceptions).
> > 
> >> By the way, my dependent variable is ordinal and my independent
> >> variables are ratio/intervalar.
> > 
> > Numeric ? Then maybe some recoding/transformation is in order ... in
> > which case Design/rms might or might not be useful.
> 
> I'm not clear on what recoding or transformation is needed for an 
> ordinal dependent variable and ratio/interval independent variables, nor 
> why rms/Design would not be useful.

I was thinking about transformations/recoding of the *independent*
variables... 

					Emmanuel Charpentier