[R] multinom and contrasts
array chip
arrayprofile at yahoo.com
Thu Apr 14 01:25:50 CEST 2005
Hi,
I found that using different contrasts (e.g.
contr.helmert vs. contr.treatment) will generate
different fitted probabilities from multinomial
logistic regression using multinom(); while the fitted
probabilities from binary logistic regression seem to
be the same. Why is that? and for multinomial logisitc
regression, what contrast should be used? I guess it's
helmert?
here is an example script:
library(MASS)
library(nnet)
#### multinomial logistic
options(contrasts=c('contr.treatment','contr.poly'))
xx<-multinom(Type~Infl+Cont,data=housing[-c(1,10,11,22,25,30),])
yy<-predict(xx,type='probs')
yy[1:10,]
options(contrasts=c('contr.helmert','contr.poly'))
xx<-multinom(Type~Infl+Cont,data=housing[-c(1,10,11,22,25,30),])
zz<-predict(xx,type='probs')
zz[1:10,]
##### binary logistic
options(contrasts=c('contr.treatment','contr.poly'))
obj.glm<-glm(Cont~Infl+Type,family='binomial',data=housing[-c(1,10,11,22,25,30),])
yy<-predict(xx,type='response')
options(contrasts=c('contr.helmert','contr.poly'))
obj.glm<-glm(Cont~Infl+Type,family='binomial',data=housing[-c(1,10,11,22,25,30),])
zz<-predict(xx,type='response')
Thanks
More information about the R-help
mailing list