Hi R-Users, I have 3 replicates ('Replicate) of counts of parasites ('nor.tot.lep') before and after an experiment ('In.Out'). I am trying to treat the three replicates as a random effect in order to determine if the main effect (In.Out) significantly influences my dependent variable (nor.tot.lep) after the variance explained by the replicates is accounted for. I have tried:
>lmer(nor.tot.lep ~ In.Out + (In.Out|Replicate),data=coho, family=poisson) Generalized linear mixed model fit using PQL Formula: nor.tot.lep ~ In.Out + (In.Out | Replicate) Data: coho Family: Poisson AIC BIC logLik deviance 849.2 867.4 -419.6 839.2 Random effects: Groups Name Variance Std.Dev. Corr Replicate (Intercept) 0.78861 0.88804 In.Out 0.67232 0.81995 -1.000 Residual 2.96308 1.72136 number of obs: 279, groups: Replicate, 3 Fixed effects: Estimate Std. Error t value (Intercept) -0.2431 0.6619 -0.3672 In.Out 1.6004 0.5645 2.8349 Correlation of Fixed Effects: (Intr) In.Out -0.975 There were 30 warnings (use warnings() to see them) > warnings() Warning messages: 1: Estimated variance-covariance for factor ‘Replicate’ is singular in: LMEopt(x = mer, value = cv) 2: nlminb returned message false convergence (8) in: LMEopt(x = mer, value = cv) but as Mr. Bates pointed out, this is inappropriate b/c I am trying to use 3 distinct replicates to estimate 3 variance-covariance parameters. "It won't work. Notice that the estimated correlation is -1.000. Your estimated variance-covariance matrix is singular" I have also tried: >glmmPQL(nor.tot.lep ~ In.Out, random = (In.Out|Replicate), family = poisson, data = coho) Error in glmmPQL(nor.tot.lep ~ In.Out, random = (In.Out | Replicate), : object "In.Out" not found and R cannot find "In.Out" If anyone has any suggestions they would be extremely appreciated! Cheers, Brendan ______________________________________________ [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 and provide commented, minimal, self-contained, reproducible code.