Message-ID: <E4D7F1B6-39F0-45E3-93BD-665D07C66106@gmail.com>
Date: 2012-07-09T19:03:43Z
From: Peter Dalgaard
Subject: Correcting for overdispersion
In-Reply-To: <9C1AC2908DCBAE4F86F810AF721915942327BA9A@icexch-m6.ic.ac.uk>
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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--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com