Hi all,

I was trying to fit a Gamma hierarchical model using "glmer", but got weird error message that I could not understand. On the other hand, a similar call to the glmmPQL leads to results that are close to what I expect. I also tried to change tha "nAGQ" argument in "glmer", but it did not solve the problem. The model I was fitting has a simple structure - one hierarchy and one offset, and I did not expect "glmer" to fail on this simple data set. Did I specify something wrong here? I appreciate any help. Thanks in advance.

#############################################################
## Code to fit the model
#############################################################
library(MASS)
library(lme4)
address <- "http://instruction.bus.wisc.edu/jfrees/jfreesbooks/Longitudinal%20and%20Panel%20Data/Book/Data/TXTData/WorkerC.txt"
wc <- read.table(address,header=T)
# clean data
cl <- unique(wc$CL[wc$LOSS==0])
wc2 <- subset(wc, !(CL %in% cl) )
# fit model
fit1 <- glmmPQL(LOSS~ YR+offset(log(PR)), random=~1|CL,family=Gamma(link="log"),
          data=wc2)
fit2 <- glmer(LOSS~ (1|CL) + YR+offset(log(PR)), family=Gamma(link="log"),
          data=wc2)


#############################################################
## Results of fit1 and fit2
#############################################################

> fit1
Linear mixed-effects model fit by maximum likelihood
  Data: wc2
  Log-likelihood: NA
  Fixed: LOSS ~ YR + offset(log(PR))
  (Intercept)            YR
-4.2830507147  0.0005085944

Random effects:
 Formula: ~1 | CL
        (Intercept)  Residual
StdDev:   0.8313193 0.5346455

Variance function:
 Structure: fixed weights
 Formula: ~invwt
Number of Observations: 700
Number of Groups: 100
> fit2
Error in asMethod(object) : matrix is not symmetric [1,2]




Wayne (Yanwei) Zhang
Statistical Research
CNA
Email: Yanwei.Zhang@cna.com<mailto:Yanwei.Zhang@cna.com>




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