[R] Error fitting overdispersed logistic regression: package dispmod
Jason Curole
jcurole at usc.edu
Sun Aug 17 20:31:34 CEST 2008
Hi all,
First, a quick thank you for R; it's amazing.
I am trying to fit models for a count dataset following the overdispersed logisitic regression approach outlined in Baggerly et al. (BMC Bioinformatics, 5:144; Annotated R code is given at the end of the paper) but R is returning an error with the data below. Any help in understanding or overcoming this obstacle is appreciated.
>library(dispmod) # required for dispersion fitting
# Now the data
>counts<-matrix(c(2,1,3,1,2715597,3296062,2945864,2215143), ncol=2)
>temp<-c(25,20,25,20) # linear factor-Temperature
>trtmnt<-c(0,0,1,1) #categorical factor
#And the models
>fit1<-glm(counts~temp+trtmnt, family="binomial")
>fit2<-glm.binomial.disp(fit1)
Binomial overdispersed logit model fitting...
Iter. 1 phi: -3.615313e-07
Error in glm(formula = counts ~ temp + trtmnt, family = "binomial", weights = disp.weights) :
negative weights not allowed
> disp.weights
[1] 54.865991 -5.218398 -15.379204 5.021180
So, clearly some dispersion weights are negative, which, according to my understanding of the model, would produce negative variances. Is there a way around this?
Thanks, Jason
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