[R] Models for Discrete Choice in R

Iuri Gavronski iuri at ufrgs.br
Tue Nov 10 10:50:00 CET 2009


Frank,

I certainly can't speak for Emmanuel. I don't know his reasons.

The reason I've posted this question is the fact that (as far as I
understood), ordinal regression is based on logistic regression (or
probit), and logistic regression expects a formula like dichotomous ~
ratio1 + ratio2 + ... + ration. However, most examples I've found in
Design, MASS and VGAM test models like ordinal ~ categorical1 +
categorical2 + ... + categoricaln.

I wonder if it is just coincidence or I have just found the wrong functions.

Best,

Iuri.

On Mon, Nov 9, 2009 at 11:43 AM, Frank E Harrell Jr
<f.harrell at vanderbilt.edu> wrote:
> Emmanuel Charpentier wrote:
>>
>> 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
>
> I realize that; still unclear.
> Frank
>
> --
> Frank E Harrell Jr   Professor and Chair           School of Medicine
>                     Department of Biostatistics   Vanderbilt University
>
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