Question on binomial data

Tue, Apr 21, 2009 4:49 AM

You should review your course material on interpreting general linear  
models. The criterion you have chosen for "significance" (looking at p  
values for indivdiual coefficients) is not the recommended one. Seek  
out the section that discusses the proper method for using deviance  
estimates for comparing nested models.

David Winsemius
On Apr 21, 2009, at 4:32 AM, ehud cohen wrote:

> Hi,
>
> We have an experiment with pass/fail outcome, and a continuous
> parameter which may contribute to the outcome.
>
> First, we've analyzed it by:
>
> p=c(F,T,F,F,F,T,T,T,T,T,T,T,F,T,T,T,T);
> w=c(53,67,59,59,53,89,72,56,65,63,62,58,59,72,61,68,63);
> l<-glm(p~w,family=binomial)
> summary(l)
>
> Which turned out to be non significant.
>
> Then, we thought of comparing the parameters of the two groups (passed
> vs. failed)
>
> t.test(w[which(p)],w[which(!p)],alternative="two.sided")
>
> which turned highly significant.
>
> I'd appreciate some insight...


David Winsemius, MD
Heritage Laboratories
West Hartford, CT

Question on binomial data

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