Dear All:

 

I am interested in multinomial logit models (function multinon, library nnet) but I'm having troubles in choose whether to define the predictors as factors or not.

 

I had posted earlier this example (thanks for the reply ronggui):

 

worms<- data.frame(year= rep(2000:2004, c(3,3,3,3,3)),age=rep(1:3,5), mud=c(2,5,0,8,7,7,5,9,14,12,8,7,5,13,11),sand=c(4,7,13,4,14,13,20,17,15,23,20,9,35,27,18), rocks=c(2,6,7,9,3,2,2,10,5,19,13,17,11,20,29))

 

k<- as.matrix(worms[,3:5])

 

(mud, sand and rocks are factors;  age and year are predictors)

 

Now there are several possibilities:

 

m1<- multinom(k~year+age,data=worms)

m2<- multinom(k~factor(year)+age,data=worms)

m3<- multinom(k~year+factor(age),data=worms)

m4<- multinom(k~factor(year)+factor(age),data=worms)

m5<- multinom(k~year:age,data=worms)

m6<- multinom(k~year*age,data=worms)

m7<- multinom(k~factor(year):age,data=worms)

m8<- multinom(k~year:factor(age),data=worms)

 

and so on.

 

 

I am far from an expert on this, and I would like to learn more about the utilization of multinom function in R and the kind of doubts I described above. So I hope that someone can recommend me some references in this matter (internet, books...) if any is available.

 

Thanks in advance, best wishes

 

Alexandre

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