Arild Husby wrote: > Dear R users, > > > I am trying to fit a GLMM to the following dataset; > > > tab > a b c > 1 1 0.6 199320100313 > 2 1 0.8 199427100412 > 3 1 0.8 199427202112 > 4 1 0.2 199428100611 > 5 1 1.0 199428101011 > 6 1 0.8 199428101111 > 7 0 0.8 199527103011 > 8 1 0.6 199527200711 > 9 0 0.8 199527202411 > 10 0 0.6 199529100412 > 11 1 0.2 199626201111 > 12 2 0.8 199627200612 > 13 1 0.4 199628100111 > 14 1 0.8 199628101511 > 15 1 0.4 199726200212 > 16 1 0.2 199726202111 > 17 1 0.6 199727101411 > 18 2 0.6 199727106911 > 19 2 0.6 199728100212 > 20 0 0.4 199820100811 > 21 1 0.8 199826200611 > 22 2 0.6 199827203811 > 23 2 1.0 200038109911 > 24 0 0.6 200126202511 > 25 0 0.4 200226100311 > 26 1 0.6 200226100411 > 27 1 0.4 200226100611 > 28 1 0.4 200226126011 > 29 1 0.4 200226203712 > 30 2 0.6 200227220313 > > > With the following model; > > lmer(a~b + (1|c), family=poisson, data=tab), > > What I want to do is to see if number of recruits (a) is dependent on the > brood sex ratio (b) including brood identity (c) as random factor. > > > However, I get the following error message; > > lmer(a~b + (1|c), family=poisson, data=tab) > Error in devAGQ(PQLpars, 1) : Unable to invert singular factor of downdated > X'X > In addition: Warning messages: > 1: optim or nlminb returned message singular convergence (7) > in: LMEopt(x = mer, value = cv) > 2: optim or nlminb returned message singular convergence (7) > in: LMEopt(x = mer, value = cv) > 3: optim or nlminb returned message singular convergence (7) > in: LMEopt(x = mer, value = cv) > 4: optim or nlminb returned message singular convergence (7) > in: LMEopt(x = mer, value = cv) > 5: optim or nlminb returned message singular convergence (7) > in: LMEopt(x = mer, value = cv) > 6: optim or nlminb returned message singular convergence (7) > in: LMEopt(x = mer, value = cv) > 7: IRLS iterations for PQL did not converge > > > I do not understand what causes this error message, all help is highly > appreciated! > > > > I am running R version 2.20 on win XPP. > >>version > > _ > platform i386-pc-mingw32 > arch i386 > os mingw32 > system i386, mingw32 > status > major 2 > minor 2.0 > year 2005 > month 10 > day 06 > svn rev 35749 > language R > > > lme4 package version: 0.98-1 > Matrix version: 0.98-7 > lattice version: 0.12-11 > > >
Is this the entire dataset or just a portion. If the former, then you have thirty groups with one observation per group. This is not reasonable for fitting GLMM. I would suggest either making the grouping variable more broad or collecting more data. Since tab$c looks like dates, maybe try: tab$c2 <- factor(substr(as.character(tab$c), 1, 4)) table(tab$c2) fit <- lmer(a ~ b + (1 | c2), tab, poisson) This works, but you still have only one observation for 1993, 2000, and 2001. HTH, --sundar ______________________________________________ [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
