Ben et. al: Shouldn't this thread be taken to R-sig-mixed-models ?
Cheers, Bert On Thu, Nov 24, 2011 at 6:14 AM, Ben Bolker <bbol...@gmail.com> wrote: > Alessio Unisi <franceschi6 <at> unisi.it> writes: > >> >> Dear R-users, >> i need help for this topic! >> >> I'm trying to determine if the reproductive success >> (0=fail, 1=success) of a species of bird >> is related to a list of covariates. >> >> These are the covariates: >> § elev: elevation of nest (meters) >> § seadist: distance from the sea (meters) >> § meanterranova: records of temperature >> § minpengS1: records of temperature >> § wchillpengS1: records of temperature >> § minpengS2: records of temperature >> § wchillpengS2: records of temperature >> § nnd: nearest neighbour distance >> § npd: nearest penguin distance >> § eggs: numbers of eggs >> § lay: laying date (julian calendar) >> § hatch: hatching date (julian calendar) >> I have some NAs in the data. >> >> I want to test the model with all the variable then i want to remove >> some, but the ideal model: >> GLM.1 <-lmer(fledgesucc ~ +lay +hatch +elev +seadist +nnd +npd >> +meanterranova +minpengS1 +minpengS2 +wchillpengS1 +wchillpengS2 >> +(1|territory), family=binomial(logit), data=fledge) >> >> doesn't work because of these errors: >> 'Warning message: In mer_finalize(ans) : gr cannot be computed at >> initial par (65)'. >> "matrix is not symmetric [1,2]" >> >> If i delete one or more of the T records (i.e. minpengS2 +wchillpengS2) >> the model works...below and example: >> >> GLM.16 <-lmer(fledgesucc ~ lay +hatch +elev +seadist +nnd +npd >> +meanterranova +minpengS1 +(1|territory), family=binomial(logit), >> data=fledge) >> >> > summary(GLM.16) >> Generalized linear mixed model fit by the Laplace approximation >> Formula: fledgesucc ~ lay + hatch + elev + seadist + nnd + npd + >> meanterranova + minpengS1 + (1 | territory) >> Data: fledge >> AIC BIC logLik deviance >> 174 204.2 -77 154 >> Random effects: >> Groups Name Variance Std.Dev. >> territory (Intercept) 0.54308 0.73694 >> Number of obs: 152, groups: territory, 96 >> > > I can't prove it, but I strongly suspect that some of your > coefficients are perfectly multicollinear. Try running your > model as a regular GLM: > > g1 <- glm(fledgesucc ~ +lay +hatch +elev +seadist +nnd +npd > +meanterranova +minpengS1 +minpengS2 +wchillpengS1 +wchillpengS2 > > and see if some of the coefficients are NA. > > coef(g1) > > lm() and glm() can handle this sort of "rank-deficient" or > multicollinear input, (g)lmer can't, as of now. > > I suspect that you may be overfitting your model anyway: > you should aim for not more than 10 observations per parameter > (in your case, since all your predictors appear to be continuous, > How many observations are left after na.omit(fledge)? > > What is the difference between your 'S1' and 'S2' temperature > records? > > ______________________________________________ > 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. > -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm ______________________________________________ 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.