[R] logistic regression tree

[Kay Cichini]

hello,

my data-collection is not yet finished, but i though have started
investigating possible analysis methods.

below i give a very close simulation of my future data-set, however there
might be more nominal explanatory variables - there will be no continous at
all  (maybe some ordered nominal..).  

i tried several packages today, but the one i fancied most was ctree of the
party package.
i can't see why the given no. of datapoints (n=100) might pose a problem
here - but please teach me better, as i might be naive..

i'd be very glad about comments on the use of ctree on suchalike dataset and
if i oversee possible pitfalls....

thank you all,
kay

######################################################################################
# an example with 3 nominal explanatory variables:
# Y is presence of a certain invasive plant species
# introduced effect for fac1 and fac3, fac2 without effect.
# presence with prob. 0.75 in factor combination fac1=I (say fac1 is geogr.
region) and  
# fac3 = a|b|c (say all richer substrates). 
# presence is not influenced by fac2, which might be vegetation type, i.e.
######################################################################################
library(party)
dat<-cbind(
expand.grid(fac1=c("I","II"),
            fac2=LETTERS[1:5],
            fac3=letters[1:10]))

print(dat<-dat[order(dat$fac1,dat$fac2,dat$fac3),])

dat$fac13<-paste(dat$fac1,dat$fac3,sep="")
for(i in 1:nrow(dat)){
ifelse(dat$fac13[i]=="Ia"|dat$fac13[i]=="Ib"|dat$fac13[i]=="Ic",
       dat$Y[i]<-rbinom(1,1,0.75),
       dat$Y[i]<-rbinom(1,1,0))
}
dat$Y<-as.factor(dat$Y)

tr<-ctree(Y~fac1+fac2+fac3,data=dat)
plot(tr)
######################################################################################


-----
------------------------
Kay Cichini
Postgraduate student
Institute of Botany
Univ. of Innsbruck
------------------------

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