Re: [R] glm with nesting

From: Doran, Harold <HDoran_at_air.org>
Date: Thu 05 Oct 2006 - 13:28:50 GMT


It's not really possible to help without knowing what errors you received and maybe some reproducible code. I think I remember this, though. From what I recall, there was no distinction between box and chick, so you cannot estimate both variance components.

> -----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 9:27 AM
> To: p.dalgaard@biostat.ku.dk
> Cc: r-help@stat.math.ethz.ch
> Subject: Re: [R] glm with nesting
>
> Peter and list,
>
> Thanks for the response. A did add box as a factor (box <-
> factor(box)). Julian should be linear - bluebird chicks are
> bluer as the season progresses from March to August.
>
> I did try the following
>
> rtot.lme <- lmer(rtot ~ sex +(purban|box:chick) +
> (purban|box), data=bb,
> na.action=na.omit) # from H. Doran
>
> and
>
> rtot.lme2 <- lme(fixed=rtot ~ sex + purban + sexv:purban,
> data = bb, random = ~1 |box) # from K. Jones <kingsfordjones@gmail.com
>
> but these did not work (months ago and I don't remember
> exactly why) and I have since seperated males and females and
> added day of the year (julian). But "|" does indicate
> grouping not nested, correct?
>
> Could someone suggest some coding that might work?
>
> Thanks again,
>
> Jeff
>
>
> >>> Peter Dalgaard <p.dalgaard@biostat.ku.dk> 10/05/06 7:14 AM >>>
> "Jeffrey Stratford" <stratja@auburn.edu> writes:
>
> > I just had a manuscript returned with the biggest problem being the
> > analysis. Instead of using principal components in a
> regression I've
> > been asked to analyze a few variables separately. So that's
> what I'm
> > doing.
>
> > I pulled a feather from young birds and we quantified
> certain aspects
> > of the color of those feathers.
>
> > Since I often have more than one sample from a nest, I thought I
> > should use a nested design.
>
> Notwithstanding comments below, that quote could be aiming
> for the fortunes package...
>
>
> > Here's the code I've been using and I'd appreciate if someone could
> > look it over and see if it was correct.
> >
> > bb.glm1 <- glm(rtot ~ box/(julian +purbank), data=bbmale,
> > family="gaussian", na.action=na.omit)

> >
> > where rtot = total reflectance, box = nest box (i.e., birdhouse),
> > julian = day of the year and purbank = the proportion of
> urban cover
> > in a 1 km buffer around the nest box. I'm not interested
> in the box effect
> > and I've seperated males and female chicks.
> >
> > I've asked about nestedness before and I was given code
> that included
> > "|" to indicate nestedness but this indicates a grouping
> does it not?
> > I suspect that there is something wrong. In the summary I get
> >
> > Coefficients:
> > Estimate Std. Error t value Pr(>|t|)
> > (Intercept) 2.880e-01 3.224e-03 89.322 <2e-16 ***
> > box -3.219e-05 6.792e-05 -0.474 0.636
> > box:julian 7.093e-08 3.971e-07 0.179 0.859
> > box:purbank -1.735e-05 1.502e-04 -0.115 0.908
>
> Several things look wrong here.
>
> Most importantly, you appear to have single-degree of freedom
> effects (t tests) of things that appear not to be linear
> effects: Certainly, you have more than two nest boxes, but
> also day of year as a linear term looks suspicious to me.
> Unless there is something I have missed completely, "box"
> should be a factor variable, and you might also need
> trigonometric terms for the julian effect (depending on what
> sort of time spans we are talking about.)
>
> Secondly, notation like box/julian suggests that julian only
> makes sense within a nest box i.e. 1st of March in one box is
> completely different from 1st of March in another box (the
> notation is more commonly used to describe bird number within
> nests and the like). And with purbank presumably constant for
> measurements from the same box, the box:purbank term looks
> strange indeed.
>
> If you want to take account of a between-box variation in the
> effect of covariates, you probably need to add them as
> variance components, but this requires non-glm software,
> either lme() or lmer(). However, instructing you on those is
> outside the scope of this mailing list, and you may need to
> find a local consultant.
>
> > The other question I have is how do I test a null hypothesis - no
> > explanatory variables? [rtot ~ NULL?]
> >
> > Many thanks,
> >
> > Jeff
> >
> >
> >
> > ****************************************
> > Jeffrey A. Stratford, Ph.D.
> > Postdoctoral Associate
> > 331 Funchess Hall
> > Department of Biological Sciences
> > Auburn University
> > Auburn, AL 36849
> > 334-329-9198
> > FAX 334-844-9234
> > http://www.auburn.edu/~stratja
> >
> 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.
> >
>
> --
> O__ ---- Peter Dalgaard ุster Farimagsgade 5, Entr.B
> c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K
> (*) \(*) -- University of Copenhagen Denmark Ph:
> (+45) 35327918
> ~~~~~~~~~~ - (p.dalgaard@biostat.ku.dk) FAX:
> (+45) 35327907
>
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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 Thu Oct 05 23:46:28 2006

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