R help - Jul 2014 - Expressing a multinomial GLM as a series of binomial GLMs

Dear all,

I am trying to express a multinomial GLM (using nnet) as a series of GLM models.

However, when I compare the multinom() predictions to those from GLM, I see
differences that I can´t
explain. Can anyone help me out here?

Here comes a reproducible example:

##
# set up data: (don´t care what they are, just for playing)
set.seed(0)
cats=c("oligolectic","polylectic","specialist","generalist")
explan1=c("natural","managed")
explan2=c("meadow","meadow","pasture","pasture")
multicats=factor(sample(cats,replace=T,100,prob=c(0.5,0.2,0.1,0.5)))
multiplan1=factor(rep(explan1,50))
multiplan2=factor(rep(explan2,25))

########################
library(nnet)
m2=multinom(multicats~multiplan1)

# predictions from multinomial model
predict(m2,type="probs")

########################
# now set up contrasts for response variable "multicats" (which has 4
levels):

ii=as.numeric(multicats)

g1=glm(I(ii%in%c(1,2)) ~ multiplan1, family = "binomial")
g2=glm(I(ii%in%c(2,3)) ~ multiplan1, family = "binomial")
g3=glm(I(ii%in%c(3,4)) ~ multiplan1, family = "binomial")

r1=predict(g1,type="response")
r2=predict(g2,type="response")
r3=predict(g3,type="response")

# calculate predictions (based on Chapter 8.3 in Dobson 2002, Introduction to
GLMs)
ee0=1/(1+r1+r2+r3)
ee1=r1/(1+r1)
ee2=r2/(1+r1+r2)
ee3=r3/(1+r1+r2+r3)

# compare predictions between GLM and multinom fits:
apply(cbind(ee0,ee1,ee2,ee3),2,mean)
apply(predict(m2,type="probs"),2,mean)


#################
[using R 3.1.1 on Windows 7 32-bit]





-- 
PD Dr. Christoph Scherber
Senior Lecturer
DNPW, Agroecology
University of Goettingen
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