[R] multinom and contrasts

[array chip]

Dear John,

Thanks for the answer! In my own dataset, The
multinom() did not converge even after I had tried to
increase the maximum number of iteration (from default
100 to 1000). In this situation, there is some bigger
diffrenece in fitted probabilities under different
contrasts (e.g. 0.9687817 vs. 0.9920816). My question
is whether the analysis (fitted probabilities) is
still valid if it does not converge? and what else can
I try about it?

Thank you!




--- John Fox <jfox at mcmaster.ca> wrote:
> Dear chip,
> 
> The difference is small and is due to computational
> error. 
> 
> Your example:
> 
> > max(abs(zz[1:10,] - yy[1:10,]))
> [1] 2.207080e-05
> 
> Tightening the convergence tolerance in multinom()
> eliminates the
> difference:
> 
> >
> options(contrasts=c('contr.treatment','contr.poly'))
> >
>
xx<-multinom(Type~Infl+Cont,data=housing[-c(1,10,11,22,25,30),],
> reltol=1.0e-12)
> # weights:  20 (12 variable)
> initial  value 91.495428 
> iter  10 value 91.124526
> final  value 91.124523 
> converged
> > yy<-predict(xx,type='probs')
> > options(contrasts=c('contr.helmert','contr.poly'))
> >
>
xx<-multinom(Type~Infl+Cont,data=housing[-c(1,10,11,22,25,30),],
> reltol=1.0e-12)
> # weights:  20 (12 variable)
> initial  value 91.495428 
> iter  10 value 91.125287
> iter  20 value 91.124523
> iter  20 value 91.124523
> iter  20 value 91.124523
> final  value 91.124523 
> converged
> > zz<-predict(xx,type='probs')
> > max(abs(zz[1:10,] - yy[1:10,]))
> [1] 1.530021e-08
> 
> I hope this helps,
>  John 
> 
> --------------------------------
> John Fox
> Department of Sociology
> McMaster University
> Hamilton, Ontario
> Canada L8S 4M4
> 905-525-9140x23604
> http://socserv.mcmaster.ca/jfox 
> -------------------------------- 
> 
> > -----Original Message-----
> > From: r-help-bounces at stat.math.ethz.ch 
> > [mailto:r-help-bounces at stat.math.ethz.ch] On
> Behalf Of array chip
> > Sent: Wednesday, April 13, 2005 6:26 PM
> > To: R-help at stat.math.ethz.ch
> > Subject: [R] multinom and contrasts
> > 
> > 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
> > 
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