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: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of > Jeffrey Stratford > Sent: Thursday, October 05, 2006 9:27 AM > To: [EMAIL PROTECTED] > 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 <[EMAIL PROTECTED] > > 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 <[EMAIL PROTECTED]> 10/05/06 7:14 AM >>> > "Jeffrey Stratford" <[EMAIL PROTECTED]> 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 Ă˜ster Farimagsgade 5, Entr.B > c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K > (*) \(*) -- University of Copenhagen Denmark Ph: > (+45) 35327918 > ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: > (+45) 35327907 > > ______________________________________________ > 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. > ______________________________________________ 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.