Jeff: > However, I have two remaining questions: (1)how concerned should I be > with the warning message below and
There was a definitive comment on this just a few days ago on the list (search the archives), the gist of it was: **very concerned** . "False convergence" means that you're not truly converged, the details for which I've forgotten (sigh...). Anyway, this means that your parameter estimates could be far from the correct minimized values = you could be in trouble. I can't help you any more than that, but hopefully you'll get responses from those with suitable expertise who can. Cheers, Bert (2) is there a way to invoke output > to get an estimate of the effect of purban2 (the proportion of urban > cover 200 m around a box) on feather color (rtot) and if there is a > difference between the sexes? I used the summary function and it > doesn't tell me much (see output below). > > I'll read up mixed models when Pinheiro arrives but any > suggestions for > diagnostics? I'm going to repeat this study and expand it by doubling > or tripling the number of birds. > > Warning message: > nlminb returned message false convergence (8) > in: "LMEoptimize<-"(`*tmp*`, value = list(maxIter = 200, tolerance = > 1.49011611938477e-08, > > > summary(eabl) > Linear mixed-effects model fit by REML > Formula: rtot ~ sexv + (purban2 | clutch) > Data: bb > AIC BIC logLik MLdeviance REMLdeviance > 5164.284 6997.864 -2052.142 4128.792 4104.284 > Random effects: > Groups Name Variance Std.Dev. Corr > > > > > clutch (Intercept) 502829 709.10 > > > > > purban20 1341990 1158.44 -0.477 > > > > > purban20.006711409 5683957 2384.10 -0.226 0.082 > > > > > purban20.01342282 1772922 1331.51 -0.386 0.176 0.067 > . > . > . > . > . > # of obs: 235, groups: clutch, 74 > > Fixed effects: > Estimate Std. Error t value > (Intercept) 5950.01 241.59 24.628 > sexvm 1509.07 145.73 10.355 > > Correlation of Fixed Effects: > (Intr) > sexvm -0.304 > > Thanks many time over, > > 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 > **************************************** > >>> "Doran, Harold" <[EMAIL PROTECTED]> 01/25/06 6:37 AM >>> > OK, we're getting somewhere. First, it looks as though (by the error > message) that you have a big dataset. My first recommendation > is to use > lmer instead of lme, you will see a significant benefit in terms of > computional speed. > > For the model this would be > > lmer(rtot ~ sexv +(purban|box:chick) + (purban|box), bb, > na.action=na.omit) > > Now, you have run out of memory. I don't know what operating > system you > are using, so go and see the appropriate FAQ for increasing memory for > your OS. > > Second, I made a mistake in my reply. Your random statement should be > random=~purban|box/chick denoting that chicks are nested in boxes, not > boxes nested in chicks, sorry about that. > > Now, why is it that each chick within box has the same value > for purban? > If this is so, why are you fitting that as a random effect? > It seems not > to vary across individual chicks, right? It seems there is only an > effect of box and not an effect for chicks. Why not just fit a random > effect only for box such as: > > rtot.lme <- lme(fixed=rtot~sexv, random=~purban2|box, > na.action=na.omit,bb) > > or in lmer > lmer(rtot ~ sexv + (purban|box), bb, na.action=na.omit) > > Harold > > > > -----Original Message----- > From: Jeffrey Stratford [mailto:[EMAIL PROTECTED] > Sent: Tue 1/24/2006 8:57 PM > To: Doran, Harold; [email protected] > Cc: > Subject: RE: [R] nested ANCOVA: still confused > > R-users and Harold. > > First, thanks for the advice; I'm almost there. > > The code I'm using now is > > library(nlme) > bb <- read.csv("E:\\eabl_feather04.csv", header=TRUE) > bb$sexv <- factor(bb$sexv) > rtot.lme <- lme(fixed=rtot~sexv, random=~purban2|chick/box, > na.action=na.omit, data=bb) > > A sample of the data looks like this > > box chick rtot purban2 sexv > 1 1 6333.51 0.026846 f > 1 2 8710.884 0.026846 m > 2 1 5810.007 0.161074 f > 2 2 5524.33 0.161074 f > 2 3 4824.474 0.161074 f > 2 4 5617.641 0.161074 f > 2 5 6761.724 0.161074 f > 4 1 7569.673 0.208054 m > 4 2 7877.081 0.208054 m > 4 4 7455.55 0.208054 f > 7 1 5408.287 0.436242 m > 10 1 6991.727 0.14094 f > 12 1 8590.207 0.134228 f > 12 2 7536.747 0.134228 m > 12 3 5145.342 0.134228 m > 12 4 6853.628 0.134228 f > 15 1 8048.717 0.033557 m > 15 2 7062.196 0.033557 m > 15 3 8165.953 0.033557 m > 15 4 8348.58 0.033557 m > 16 2 6534.775 0.751678 m > 16 3 7468.827 0.751678 m > 16 4 5907.338 0.751678 f > 21 1 7761.983 0.221477 m > 21 2 6634.115 0.221477 m > 21 3 6982.923 0.221477 m > 21 4 7464.075 0.221477 m > 22 1 6756.733 0.281879 f > 23 2 8231.496 0.134228 m > > The error I'm getting is > > Error in logLik.lmeStructInt(lmeSt, lmePars) : > Calloc could not allocate (590465568 of 8) memory > In addition: Warning messages: > 1: Fewer observations than random effects in all level 2 groups in: > lme.formula(fixed = rtot ~ sexv, random = ~purban2 | chick/box, > 2: Reached total allocation of 382Mb: see help(memory.size) > > There's nothing "special" about chick 1, 2, etc. These were > simply the > order of the birds measured in each box so chick 1 in box 1 > has nothing > to do with chick 1 in box 2. > > 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 > **************************************** > >>> "Doran, Harold" <[EMAIL PROTECTED]> 01/24/06 2:04 PM >>> > Dear Jeff: > > I see the issues in your code and have provided what I think > will solve > your problem. It is often much easier to get help on this > list when you > provide a small bit of data that can be replicated and you state what > the error messages are that you are receiving. OK, with that > said, here > is what I see. First, you do not need to use the syntax bb$sex in your > model, this can be significantly simplified. Second, you do not have a > random statement in your model. > > Here is your original model: > lme(bb$rtot~bb$sex, bb$purban|bb$chick/bb$box, na.action=na.omit) > > Here is what it should be: > > lme(fixed = rtot~sex, random=~purban|chick/box, na.action=na.omit, > data=bb) > > Notice there is a fixed and random call. You can simplify this as > > lme(rtot~sex, random=~purban|chick/box, na.action=na.omit, bb) > > Note, you can eliminate the "fixed=" portion but not the random > statement. > > Last, if you want to do this in lmer, the newer function for mixed > models in the Matrix package, you would do > > lmer(rtot~sex + (purban|box:chick) + (purban|box), na.action=na.omit, > data=bb) > > Hope this helps. > Harold > > > > > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of > Jeffrey Stratford > Sent: Tuesday, January 24, 2006 11:34 AM > To: [email protected] > Subject: [R] nested ANCOVA: still confused > > Dear R-users, > > I did some more research and I'm still not sure how to set up > an ANCOVA > with nestedness. Specifically I'm not sure how to express > chicks nested > within boxes. I will be getting Pinheiro & Bates (Mixed > Effects Models > in S and S-Plus) but it will not arrive for another two weeks from our > interlibrary loan. > > The goal is to determine if there are urbanization (purban) effects on > chick health (rtot) and if there are differences between > sexes (sex) and > the effect of being in the same clutch (box). > > The model is rtot = sex + purban + (chick)box. > > I've loaded the package lme4. And the code I have so far is > > bb <- read.csv("C:\\eabl\\eabl_feather04.csv", header=TRUE) bb$sex <- > factor(bb$sex) rtot.lme <- lme(bb$rtot~bb$sex, > bb$purban|bb$chick/bb$box, > na.action=na.omit) > > but this is not working. > > Any suggestions would be greatly appreciated. > > 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 > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
