First of all I'm forwarding this mail to the R-SIG-mixed-models, which is more appropriate to your question.
Remember that family = bionomial uses by default the logit link. Hence all parameters will be on the logit scale. So you will need to backtransform them for comparison. Then you'll see that the parameters are much closer to the averages. They still differ, but that is due to the difference in model. Your averages are essentially something like summary(model1<-glm(cbind(VisitsExpTree,TotalVisits-VisitsExpTree)~ treatment +(1|Individual), family=binomial, data=r)) > library(boot) > intercept <- 0.37228 > treatmentb <- 0.03367 > treatmentc <- -0.60606 > treatmentd <- -0.25504 > inv.logit(intercept) [1] 0.5920098 > inv.logit(intercept + treatmentb) [1] 0.6001164 > inv.logit(intercept + treatmentc) [1] 0.4418197 > inv.logit(intercept + treatmentd) [1] 0.5292765 HTH, Thierry ------------------------------------------------------------------------ ---- ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology and quality assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32 54/436 185 [EMAIL PROTECTED] 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: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Namens RFTW Verzonden: vrijdag 19 september 2008 8:16 Aan: r-help@r-project.org Onderwerp: Re: [R] Mixed effects model with binomial errors - problem anyone? RFTW wrote: > > ok... the model now runs properly (say, without errors). Now about the > result. > These are the averages per treatments > > tapply(VecesArbolCo.VecesCo.C1,T2,mean) > a b c d > 0.49 0.56 0.45 0.58 > > > I run this very simple model > >> summary(model1<-lmer(cbind(VisitsExpTree,TotalVisits-VisitsExpTree)~ >> treatment +(1|Individual), family=binomial, data=r)) > > Generalized linear mixed model fit by the Laplace approximation > Formula: cbind(VisitsExpTree,TotalVisits-VisitsExpTree)~ treatment > +(1|Individual) > Data: r > AIC BIC logLik deviance > 242.3 255.9 -116.2 232.3 > Random effects: > Groups Name Variance Std.Dev. > Individuo (Intercept) 0.14075 0.37517 > Number of obs: 112, groups: Individuo, 37 > > Fixed effects: > Estimate Std. Error z value Pr(>|z|) > (Intercept) 0.37228 0.19031 1.9562 0.05044 . > treatmentb 0.03367 0.24520 0.1373 0.89079 > treatmentc -0.60606 0.23330 -2.5978 0.00938 ** > treatmentd -0.25504 0.22790 -1.1191 0.26311 > --- > Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 > > Correlation of Fixed Effects: > (Intr) T2b T2c > T2b -0.675 > T2c -0.697 0.543 > T2d -0.720 0.544 0.581 > > > wouldnt we expect the intercept to be roughtly the mean of treatment a? > and thus the estimate of treatmentb to be +0.07, c: -0.04 and d: +0.09 > roughly? > > Is this model just completely not estimating well, or are the estimates > not the 'real values'. > > I tried to get teh predict function to give me the 4 predicted values > based on the model, but i havent succeeded in doing so. maybe someone can > help me on that one too (predict(model1,type="response") doesnt work) > > thnx > -- View this message in context: http://www.nabble.com/Mixed-effects-model-with-binomial-errors----proble m-tp19413327p19566778.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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. Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is door een geldig ondertekend document. The views expressed in this message and any annex are purely those of the writer and may not be regarded as stating an official position of INBO, as long as the message is not confirmed by a duly signed document. ______________________________________________ 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.
