[R] Regression models for ordinal responses ??
John Fox
jfox at mcmaster.ca
Fri May 3 13:43:40 CEST 2002
At 09:50 AM 5/3/2002 +0200, you wrote:
>Hello list,
>
>Is there any mean to fit models for ordinal response other than multinomial
>polytomous ("multinom" from nnet ) and cumulative logit ("polr" from MASS)?
>I am particularly interested in continuation-ratio model and
>adjacent-category logit model. It is for the sake of epidemiology in
>wild-living populations!
Dear Emmaneulle,
Continuation-ratio models are just a collection of binomial (or binary)
logit models, each of which can be fit with glm. So, for example, if you
have categories A, B, and C, you'd fit a model in which the response is A
vs. (B or C), and another in which the response is B vs. C. In the second
model, the response if NA for those in category A. The models are
independent, so, for example, you can add corresponding log-likelihood
ratio statistics and df.
I believe that the adjacent-categories logit model is equivalent to the
multinomial logit model. To get the coefficients for the log-odds of
category i vs. i + 1 [i.e., log(pi_i/pi_{i+1})], subtract the multinomial
logit coefficients for category i + 1 (vs. the baseline) from the
coefficients for category i. (You should check that this is right -- I
might not remember it correctly.)
I hope that this helps,
John
-----------------------------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario, Canada L8S 4M4
email: jfox at mcmaster.ca
phone: 905-525-9140x23604
web: www.socsci.mcmaster.ca/jfox
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