[R] Problem on glmer

[Dennis Murphy]

Hi:

This might be helpful:

http://glmm.wikidot.com/faq

It has some commentary and potential workarounds re gamma GLMMs toward
the bottom of the page. I might also suggest that r-sig-mixed-models
might be a better forum for these types of questions; you can
subscribe by going to

http://www.r-project.org/mail.html

and scrolling down a bit to where the special interest groups are
listed. Same process as subscribing to R-help.

Dennis


On Tue, May 17, 2011 at 7:17 AM, Zhang,Yanwei <Yanwei.Zhang at cna.com> wrote:
> Hi Dennis,
>
> Thanks for your input. I am quite shocked that the Gamma model is not implemented in glmer yet, but do you happen to know if there is other packages in R that could fit Gamma hierarchical models besides MASS? The glmmPQL results are a bit off compared to what have been published.  Thanks.
>
>
>
> Wayne (Yanwei) Zhang
> Statistical Research
>>CNA
>
> -----Original Message-----
> From: Dennis Murphy [mailto:djmuser at gmail.com]
> Sent: Tuesday, May 17, 2011 3:05 AM
> To: Zhang,Yanwei
> Cc: r-help at r-project.org
> Subject: Re: [R] Problem on glmer
>
> Hi:
>
> I believe that the problem with the glmer() call is that you are
> invoking the Gamma family, which appears not to be implemented at
> present. See
>
> http://r-project.markmail.org/search/?q=r-sig-mixed-models#query:r-sig-mixed-models%20date%3A201105%20+page:8+mid:q2b2uoupejdzmvtl+state:results
>
> Dennis
>
> On Mon, May 16, 2011 at 3:31 PM, Zhang,Yanwei <Yanwei.Zhang at cna.com> wrote:
>> 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 at cna.com<mailto:Yanwei.Zhang at cna.com>
>>
>>
>>
>>
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>
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