[R] analyzing binomial data with spatially correlated errors

From: Jean-Baptiste Ferdy <Jean-Baptiste.Ferdy_at_univ-montp2.fr>
Date: Wed, 19 Mar 2008 17:02:12 +0100


Dear R users,

I want to explain binomial data by a serie of fixed effects. My problem is that my binomial data are spatially correlated. Naively, I thought I could found something similar to gls to analyze such data. After some reading, I decided that lmer is probably to tool I need. The model I want to fit would look like

lmer ( cbind(n.success,n.failure) ~ (x1 + x2 + ... + xn)^2 , family=binomial, correlation=corExp(1,form=~longitude+latitude))

This doesn't work because lmer says it needs a random effect in the model. And, apart from the spatial random effect that I want to capture by computing the correlation matrix, I have no other random effect.

There must be something I do not understand here... I can't get why gls can do this on gaussian data but lmer can't on binomial ones.

Any help or thought on this would be welcome !

-- 
Jean-Baptiste Ferdy
Institut des Sciences de l'Évolution de Montpellier
CNRS UMR 5554
Université Montpellier 2
34 095 Montpellier cedex 05
tel. +33 (0)4 67 14 42 27
fax  +33 (0)4 67 14 36 22

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Received on Wed 19 Mar 2008 - 16:07:34 GMT

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