From daniel.sabanesbove at gmx.net  Wed Jan  7 13:41:54 2009
From: daniel.sabanesbove at gmx.net (=?ISO-8859-1?Q?Daniel_Saban=E9s_Bov=E9?=)
Date: Wed, 07 Jan 2009 13:41:54 +0100
Subject: [Rd] Apparant bug in binomial model in GLM (PR#13434)
In-Reply-To: <mailman.25.1231326005.26300.r-devel@r-project.org>
References: <mailman.25.1231326005.26300.r-devel@r-project.org>
Message-ID: <4964A312.4070103@gmx.net>

> There appear to be a bug in the estimation of significance in the binomial model
> in GLM. This bug apparently appears when the correlation between two variables
> is to strong.
>
> Such as this dummy example
> c(0,0,0,0,0,1,1,1,1,1)->a
> a->b
> m1<-glm(a~b, binomial)
> summary(m1)
>
> It is sufficient that all 1's correspond to 1's such as this example
Isn't this just the well-known failure of logistic regression (non-existence of maximum likelihood estimator) for linearly separable data? (b > 0.5 => a == 1)
> c(0,0,0,0,0,1,1,1,1,1)->a
> c(0,0,0,0,1,1,1,1,1,1)->c
> m1<-glm(a~c, binomial)
> summary(m1)
This is not linearly separable, but almost, so the standard errors will be very large.



[Rd] Apparant bug in binomial model in GLM (PR#13434)
=?ISO-8859-1?Q?Daniel_Saban=E9s_Bov=E9?=