[R] glmmBUGS: logistic regression on proportional data
dwinsemius at comcast.net
Sun Feb 8 18:31:55 CET 2009
Installing the glmmBUGS package and a bit of experimentation produces
this minor modification of your code that seems to run without error.
It's back to you to see if the output is sensible.
Newdat<-data.frame(Newtree=rep(1:3, each=20), Newsect=rep(c("a","b"),
each=10), Newdist=rep(1:5, 2),
y=rpois(60,2), tot=rep(c(14,12,10,8,6), 12))
mod<-glmmBUGS(y/tot~Newsect + Newdist, effects="Newtree",
I am guessing that the interpreter was looking for a variable yseed
within Newdat and not finding it. It, however, is able to "see" y and
tot within Newdat. Also appears that using cbind(y, tot) on the LHS of
hte formula will avoid the error you were getting.
On Feb 8, 2009, at 8:29 AM, John Poulsen wrote:
> I am trying to run a logistic regression with random effects on
> proportional data in glmmBUGS. I am a newcomer to this package, and
> wondered if anyone could help me specify the model correctly.
> I am trying to specify the response variable, /yseed/, as # of
> successes out of total observations... but I suspect that given the
> error below, that is not correct. Also, Newsect should be a factor,
> whereas Newdist is continuous.
> Newdat<-data.frame(Newtree=rep(1:3, each=20),
> Newsect=rep(c("a","b"), each=10), Newdist=rep(1:5, 2),
> y=rpois(60,2), tot=rep(c(14,12,10,8,6), 12))
> yseed<-cbind(Newdat$y, Newdat$tot)
> mod<-glmmBUGS(yseed~Newsect + Newdist, effects="Newtree",
> family="binomial", data=Newdat)
> Error in `[.data.frame`(data, , response, drop = FALSE) :
> undefined columns selected
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