From: Ville Koskinen <ville.koskinen_at_matrex.fi>

Date: Wed 15 Jun 2005 - 02:22:56 EST

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R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Wed Jun 15 02:25:58 2005

Date: Wed 15 Jun 2005 - 02:22:56 EST

Sex Age pr(A) pr(B) pr(C) pr(D) ... 1 11 0.5 0.5 0 0 1 40 1 0 0 0 0 34 0 0 0 1 0 64 0.1 0.5 0.2 0.2

I have been able to model a case with only two alternatives "A" and "not A" by using glm().

I do not know what functions are available to estimate such a model with more than two alternatives. Multinom() is one possibility, but it only allows the use of binary 0/1-data instead of observed probabilities. Did I understand this correctly?

Additionally, I am willing to use different independent variables for the
different alternatives in the model. Formally, I mean that:
Pr(A)=exp(uA)/(exp(uA)+exp(uB)+exp(uC)+exp(uD)
Pr(B)=exp(uB)/(exp(uA)+exp(uB)+exp(uC)+exp(uD)

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where uA, uB, uC and uD are linear functions with different independent
variables, e.g. uA=alpha_A1*Age, uB=alpha_B1*Sex.

Do you know how to estimate this type of models in R?

Best regards, Ville Koskinen

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Wed Jun 15 02:25:58 2005

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