R help - Jul 2012 - Correcting for overdispersion

Hello,

I am trying to determine LD50 and LD95 using dose.p in MASS however some of the
Residual variance is larger than the degrees of freedom. Please can anyone help
with any advice as to how i can correct for this?

Here is the model as inputted into R



y<-cbind(dead,n-dead)

model<-glm(y~log(conc),binomial)
summary(model)

xv<-seq(min(log(conc)-1),max(log(conc)+1),0.01)
lines(xv,predict(model,list(conc=exp(xv)),type="response"))

dose.p(model,p=c(0.10,0.25,0.5,0.75,0.90,0.95))



Thanks

Adaku



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On Jul 9, 2012, at 20:23 , Lawrence, Adaku wrote:
> Hello,
> 
> I am trying to determine LD50 and LD95 using dose.p in MASS however some of
the Residual variance is larger than the degrees of freedom. Please can anyone
help with any advice as to how i can correct for this?
Er, in what sense is that a problem? Your code is not reproducible, at least
some output to look at might help.

-pd
> 
> Here is the model as inputted into R
> 
> 
> 
> y<-cbind(dead,n-dead)
> 
> model<-glm(y~log(conc),binomial)
> summary(model)
> 
> xv<-seq(min(log(conc)-1),max(log(conc)+1),0.01)
> lines(xv,predict(model,list(conc=exp(xv)),type="response"))
> 
> dose.p(model,p=c(0.10,0.25,0.5,0.75,0.90,0.95))
> 
> 
> 
> Thanks
> 
> Adaku
> 
> 
> 
> 	[[alternative HTML version deleted]]
> 
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