[R] Problem specifying Gamma distribution in lme4/glmer

[Ben Bolker]

Matthew Giovanni <matthewgiovanni <at> gmail.com> writes:

> 
> Dear R and lme4 users-
> 
> I am trying to fit a mixed-effects model, with the glmer function in
> lme4, to right-skewed, zero-inflated, non-normal data representing
> understory grass and forb biomass (continuous) as a function of tree
> density (indicated by leaf-area).  Thus, I have tried to specify a
> Gamma distribution with a log-link function but consistently receive
> an error as follows:
> 
> total=glmer(total~gla4+(1|plot)+
    (1|year/month),data=veg,family=Gamma(link=log))
> summary(total)
> Error in asMethod(object) : matrix is not symmetric [1,2]
> 
> I have also tried fitting glmm's with lme4 and glmer to other
> Gamma-distributed data but receive the same error.  Has anyone had
> similar problems and found any solutions?

 1. probably best to post questions like this to 
r-sig-mixed-models at r-project.org

 2. haven't seen this particular problem.  Can you please
provide a reproducible example (post your data, or a small
subset of your data, or a simulated example that displays
the same problem), and give the results of
the sessionInfo() function?

f <- factor(rep(1:10,each=10))
x <- runif(100)
dat <- data.frame(x,f)
library(lme4)
 [snip messages]
g1 <- glmer(x~1+(1|f),data=dat,family=Gamma(link=log))
  Generalized linear mixed model fit by the Laplace approximation 
  [...]
summary(g1)
  [ works fine]

sessionInfo()
  R version 2.10.1 (2009-12-14) 
  i486-pc-linux-gnu 

  [snip]

  other attached packages:
  [1] lme4_0.999375-32-2 Matrix_0.999375-38 lattice_0.18-3    

 3. zero-inflated data may not be particularly well-represented
by a Gamma distribution: if you actually have a significant number
of exactly-zero values, you may want to analyze your data in two
stages, first as a presence-absence problem and then as a conditional
density (i.e., what is the distribution of the non-zero values)?