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glm or glmm?

To: s-news@lists.biostat.wustl.edu
Subject: glm or glmm?
From: Henrik Parn <parn@nt.ntnu.no>
Date: Mon, 20 Dec 2004 17:08:12 +0100
Reply-to: parn@nt.ntnu.no
User-agent: Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.6) Gecko/20040113
Dear S-users,

I am working on a bird where a female either mate with her social partner, or with other males in the surrounding territories. The offspring in a nest thus all have the same mother, but can be sired by one or more males. I divide the offspring into two groups: within-pair offspring (WPO) or extra-pair offspring (EPO). My data set is arranged with one female (nest) per row and with data on: number of WPO, number of EPO and different female traits.

My object is to relate the proportion of extra-pair offspring in a nest to different traits off the mother. I have defined an EP-offspring as success, and WP-offspring as failure. I first planned to use an ordinary glm:
y<-cbind(number of EPO, number of WPO)
glm(y~mother.trait, family=binomial)

However, now I am a unsure whether I need to include 'mother ID' as a random factor. I.e whether to treat the respons variable (EPO vs WPO per nest) as a single measure per female. Or should I instead 'imagine' the response as several measures per female: one measure (EPO or WPO) per offspring in her nest, and all offspring in her nest having the same random factor 'mother ID'? If I need a random factor, which glmm do you suggest?

Thank you for your help!

Sincerely,
Henrik
--
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Henrik Pärn
Department of Biology
NTNU
7491 Trondheim
Norway

+47 735 96282 (office)
+47 909 89 255 (mobile)
+47 735 96100 (fax)
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