Thank you Thierry for your kind answer! If you don't mind I would like to ask a follow-up question. In your suggestions I get P-values for "Species". However, I am really not interested in that factor per se. Would it make sense to use this model instead if I am only interested in "Genotype"?
> model<-glmer(Nymphs~Genotype+(1|Species/Genotype),family=poisson) All the best, Johan 2011/3/9 ONKELINX, Thierry <thierry.onkel...@inbo.be>: > Dear Johan, > > A few remarks. > > - R-sig-mixed models is a better list for asking questions about mixed model. > - I presume that Nymphs is the number of insects? In that case you need a > generalised linear (mixed) model with poisson family > - What are you interessed in? The variability among genotypes or the effect > of each genotype. > You can achieve the first with a glmm like glmer(Nymphs ~ Species + > (1|Genotype), family = "poisson"). Genotype will be implicitly nested in > Species. Note that since you have only 4 genotypes, you will not get very > reliable estimates of the genotype variance. > For the latter you cannot use a mixed model so you need a simple > glm(Nymphs ~ Species/Genotype, family = "poisson"). Note that several > coefficients will be NaN, because you cannot estimate them. > > Best regards, > > Thierry > > ---------------------------------------------------------------------------- > ir. Thierry Onkelinx > Instituut voor natuur- en bosonderzoek > team Biometrie & Kwaliteitszorg > Gaverstraat 4 > 9500 Geraardsbergen > Belgium > > Research Institute for Nature and Forest > team Biometrics & Quality Assurance > Gaverstraat 4 > 9500 Geraardsbergen > Belgium > > tel. + 32 54/436 185 > thierry.onkel...@inbo.be > www.inbo.be > > To call in the statistician after the experiment is done may be no more than > asking him to perform a post-mortem examination: he may be able to say what > the experiment died of. > ~ Sir Ronald Aylmer Fisher > > The plural of anecdote is not data. > ~ Roger Brinner > > The combination of some data and an aching desire for an answer does not > ensure that a reasonable answer can be extracted from a given body of data. > ~ John Tukey > > >> -----Oorspronkelijk bericht----- >> Van: r-help-boun...@r-project.org >> [mailto:r-help-boun...@r-project.org] Namens Johan Stenberg >> Verzonden: dinsdag 8 maart 2011 16:52 >> Aan: r-help@r-project.org >> Onderwerp: [R] NaNs in Nested Mixed Model >> >> Dear R users, >> >> I have a problem with something called "NaNs" in a nested mixed model. >> >> The background is that I have studied the number of insect >> nymphs emerging from replicated Willow genotypes in the >> field. I have 15 replicates each of 4 Willow genotypes >> belonging two 2 Willow species. >> Now I want to elucidate the effect of Willow genotype on the >> number of emerging nymphs. Previously I performed a simple >> one-way anova with "genotype" as explanatory factor and >> "number of nymphs emerging" as dependent variable, but the >> editor of the journal I've submitted this piece to wants me >> to nest Willow genotype within Willow species before he >> accepts the paper for publication [Species*Genotype(Species)]. >> >> The fact that I didn't include "Willow species" as a factor >> in my initial analysis reflects that I am not very interested >> in the species factor per se - I am just interested in if >> genetic variation in the host plant is important, but >> "species" is of course a factor that structures genetic diversity. >> >> I thought the below model would be appropriate: >> >> > model<-lme(Nymphs~Species*Genotype,random=~1|Species/Genotype) >> >> ...but I then get the error message "Error in MEEM(object, conLin, >> control$niterEM) : Singularity in backsolve at level 0, block 1" >> >> I then tried to remove "Genotype" from the fixed factors, but >> then I get the error message "NaNs produced". >> >> > model<-lme(Nymphs~Species,random=~1|Species/Genotype) >> > summary(model) >> Linear mixed-effects model fit by REML >> Data: NULL >> AIC BIC logLik >> 259.5054 269.8077 -124.7527 >> >> Random effects: >> Formula: ~1 | Species >> (Intercept) >> StdDev: 0.9481812 >> >> Formula: ~1 | Genotype %in% Species >> (Intercept) Residual >> StdDev: 0.3486937 1.947526 >> >> Fixed effects: Nymphs ~ Species >> Value Std.Error DF t-value p-value >> (Intercept) 2.666667 1.042243 56 2.558585 0.0132 >> Speciesviminalis -2.033333 1.473954 0 -1.379510 NaN >> Correlation: >> (Intr) >> Speciesviminalis -0.707 >> >> Standardized Within-Group Residuals: >> Min Q1 Med Q3 Max >> -1.4581821 -0.3892233 -0.2751795 0.3439871 3.1630658 >> >> Number of Observations: 60 >> Number of Groups: >> Species Genotype %in% Species >> 2 4 >> Warning message: >> In pt(q, df, lower.tail, log.p) : NaNs produced >> *********** >> >> Do you have any idea what these error messages mean in my >> case and how I can get around them? >> >> Thank you on beforehand! (data set attached). >> >> Johan >> ______________________________________________ R-help@r-project.org 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.
