Re: [R] glm with nesting

From: Berton Gunter <gunter.berton_at_gene.com>
Date: Thu 05 Oct 2006 - 15:21:23 GMT


Jeffrey:

Please... May I repeat what Peter Dalgaard already said: consult a local statistician. The structure of your study is sufficiently complicated that your stat 101 training is inadequate. Get professional help, which this list is not set up to provide (though it often does, through the good offices and patience of many wise contributors).

Bert Gunter
Genentech Nonclinical Statistics
South San Francisco, CA 94404  

> -----Original Message-----
> From: r-help-bounces@stat.math.ethz.ch
> [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of
> Jeffrey Stratford
> Sent: Thursday, October 05, 2006 7:46 AM
> To: HDoran@air.org; r-help@stat.math.ethz.ch
> Subject: Re: [R] glm with nesting
>
> Harold and list,
>
> I've changed a few things since the last time so I'm really starting
> from scratch.
>
> I start with
>
> bbmale <- read.csv("c:\\eabl\\2004\\feathers\\male_feathers2.csv",
> header=TRUE)
> box <-factor(box)
> chick <- factor(chick)
>
> Here's a sample of the data
>
> box,chick,julian,cltchsz,mrtot,cuv,cblue,purbank,purban2,purba
> n1,pgrassk,pgrass2,pgrass1,grassdist,grasspatchk
> 1,2,141,2,21.72290152,0.305723811,0.327178868,0.003813435,0.02
> 684564,0.06896552,0.3282487,0.6845638,0.7586207,0,3.73
> 4,1,164,4,18.87699007,0.281863299,0.310935559,0.06072162,0.208
> 0537,0.06896552,0.01936052,0,0,323.1099,0.2284615
> 4,2,164,4,19.64359348,0.294117388,0.316049817,0.06072162,0.208
> 0537,0.06896552,0.01936052,0,0,323.1099,0.2284615
> 7,1,118,4,13.48699876,0.303649408,0.31765218,0.3807568,0.43624
> 16,0.6896552,0.06864183,0.03355705,0,94.86833,0.468
> 12,1,180,4,21.42196378,0.289731361,0.317562294,0.09238011,0.13
> 42282,0,0.2430127,0.8322148,1,0,1.199032
> 12,2,180,4,18.79487905,0.286052077,0.316367349,0.09238011,0.13
> 42282,0,0.2430127,0.8322148,1,0,1.199032
> 12,3,180,4,12.83127682,0.260197475,0.292636914,0.09238011,0.13
> 42282,0,0.2430127,0.8322148,1,0,1.199032
> 15,1,138,4,20.07161467,0.287632782,0.318671887,0.07046477,0.03
> 355705,0.03448276,0.2755622,0.6577181,0.8275862,0,1.503818
> 15,2,138,4,17.61146256,0.305581768,0.315848051,0.07046477,0.03
> 355705,0.03448276,0.2755622,0.6577181,0.8275862,0,1.503818
> 15,3,138,4,20.36397134,0.271795667,0.30539683,0.07046477,0.033
> 55705,0.03448276,0.2755622,0.6577181,0.8275862,0,1.503818
> 15,4,138,4,20.81940158,0.269468041,0.304160648,0.07046477,0.03
> 355705,0.03448276,0.2755622,0.6577181,0.8275862,0,1.503818
>
> As you can see I have multiple boxes (> 70). Sometimes I
> have multiple
> chicks per box each having their own response to mrtot, cuv,
> and cblue
> but the same landscape variables for that box. Chick number
> is randomly
> assigned and is not an effect I'm interested in. I'm really not
> interested in the box effect either. I would like to know if
> landscape
> affects the color of chicks (which may be tied into chick
> health/physiology). We also know that chicks get bluer as the season
> progresses and that clutch size (cltchsz) has an effect so
> I'm including
> that as covariates.
>
> Hopefully, this clears things up a bit.
>
> I do have the MASS and MEMS (Pineiro's) texts in hand.
>
> Many thanks,
>
> Jeff
>
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>



R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Fri Oct 06 01:37:26 2006

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