R help - Jan 2006 - mixed effects models - negative binomial family?

Hello all,

I would like to fit a mixed effects model, but my response is of the  
negative binomial (or overdispersed poisson) family. The only (?)  
package that looks like it can do this is glmm.ADMB (but it cannot  
run on Mac OS X - please correct me if I am wrong!) [1]

I think that glmmML {glmmML}, lmer {Matrix}, and glmmPQL {MASS} do  
not provide this "family" (i.e. nbinom, or overdispersed poisson). Is
there any other package that offers this functionality?

Thanking you in advance,

Costas


[1] Yes, I know I can use this on another OS. But it is kind of a  
nuisance, as I have my whole workflow setup on a mac, including emacs 
+ess, the data etc etc. It will be non-trivial to start moving/ 
syncing files between >1 computers, in order to use this package...

--
Constantinos Antoniou, Ph.D.
Department of Transportation Planning and Engineering
National Technical University of Athens
5, Iroon Polytechniou str. GR-15773, Athens, Greece

Constantinos Antoniou <antoniou <at> central.ntua.gr> writes:
> 
> Hello all,
> 
> I would like to fit a mixed effects model, but my response is of the  
> negative binomial (or overdispersed poisson) family. The only (?)  
> package that looks like it can do this is glmm.ADMB (but it cannot  
> run on Mac OS X - please correct me if I am wrong!) [1]
> 
> I think that glmmML {glmmML}, lmer {Matrix}, and glmmPQL {MASS} do  
> not provide this "family" (i.e. nbinom, or overdispersed
poisson). Is
> there any other package that offers this functionality?
 You'll probably get more complete/informed information
shortly, but ... you may not be able to get a negative
binomial distribution per se, but other versions
of "overdispersed Poisson" are indeed possible.  glmmPQL
will let you use the quasipoisson family, which allows for
overdispersion in a phenomenological way; more mechanistically,
observation-level random effects on the scale of the
linear predictor (log for a GLMM with family=poisson)
lead to a lognormal-Poisson distribution, which has similar
properties to the NB.  I suspect you can do this in lmer
(lme4 package), which does GLMMs if you specify the family
argument.

See:

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11393830&dopt=Abstract
(analysis done in SAS but probably completely feasible in R at this point)

  Ben

Have you tried nlme?
   
  I tried to something similar.
   
  Here is the code that I used for a negative binomial random effects model
   
   
  library(nlme)
  mydata<-read.table("C:\\Plx\\plx.all\\plxall.txt",header=TRUE)
  loglike =
function(PLX_NRX,PD4_42D,GAT_34D,VIS_42D,MSL_42D,SPE_ROL,XM2_DUM,THX_DUM,b0,b1,b2,b3,b4,b5,b6,b7,alpha){
  lambda = exp(b0 +
b1*GAT_34D+b2*VIS_42D+b3*MSL_42D+b4*PD4_42D+b5*SPE_ROL+b6*XM2_DUM+b7*THX_DUM)
  y=round(PLX_NRX)
  y <- table(y)
   freq <- as.vector(y)
          count <- as.numeric(names(y))
   count <- count[!(freq < 1)]
      freq <- freq[!(freq < 1)]
      n <- length(count)
      df <- n - 1
                          
   
   
   
   df <- df - 2
              xbar <- weighted.mean(count, freq)
              s2 <- var(rep(count, freq))
              p <- xbar/s2
              alpha <- xbar^2/(s2 - xbar)
   
  ( dnbinom(y,alpha,(alpha/(alpha+lambda))) )
    }
   
   
 
plx.nlme<-nlme(PLX_NRX~loglike(PLX_NRX,PD4_42D,GAT_34D,VIS_42D,MSL_42D,SPE_ROL,XM2_DUM,THX_DUM,b0,b1,b2,b3,b4,b5,b6,b7,alpha),
  data=mydata,
  fixed=list(b0 + b1+b2+b3+b4+b5+b6+b7+alpha~1),
  random=b0~1|menum,
   
  start=c(b0=0,b1=0,b2=0,b3=0,b4=0,b5=0,b6=0,b7=0,alpha=5)
  )
   
  I am not sure that this is what you are looking for , but I hope this helps!

   
  Elizabeth Lawson
Constantinos Antoniou <antoniou@central.ntua.gr> wrote:
  Hello all,

I would like to fit a mixed effects model, but my response is of the 
negative binomial (or overdispersed poisson) family. The only (?) 
package that looks like it can do this is glmm.ADMB (but it cannot 
run on Mac OS X - please correct me if I am wrong!) [1]

I think that glmmML {glmmML}, lmer {Matrix}, and glmmPQL {MASS} do 
not provide this "family" (i.e. nbinom, or overdispersed poisson). Is 
there any other package that offers this functionality?

Thanking you in advance,

Costas


[1] Yes, I know I can use this on another OS. But it is kind of a 
nuisance, as I have my whole workflow setup on a mac, including emacs 
+ess, the data etc etc. It will be non-trivial to start moving/ 
syncing files between >1 computers, in order to use this package...

--
Constantinos Antoniou, Ph.D.
Department of Transportation Planning and Engineering
National Technical University of Athens
5, Iroon Polytechniou str. GR-15773, Athens, Greece

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