R help - Sep 2007 - Correlated frailty model

Dear R-help,
I am trying to a estimate a correlated frailty model. My dataset is 
made up of 40000 observations. I would like to know if it is too big or 
I have done some mistakes in the following code.

group<-paste(usa$id,usa$mob)
mixed.logn<-coxme(Surv(yearspan)~ south+mod, data=usa,random= ~ 1|group)
Errore in matrix(0, dd[1], dd[2], dimnames = x at .Dimnames) :        non 
? possibile allocare un vettore di lunghezza 1600000000
(It is not possible to use a vector of leght 1600000000)
Inoltre(Also): Warning message:
The initial fit took 6  steps, which is bigger than the inner.iter  
paramter.  Consider increasing the latter in: coxme.fit(X, Y, strats, 
offset, init, control, weights = weights,  Thank you
Silvia

>  I am trying to a estimate a correlated frailty model. My dataset is 
> made up of 40000 observations. I would like to know if it is too big or 
> I have done some mistakes in the following code.
  I have used larger data sets successfully.  I need to know a little bit
more about our problem.
> coxme(Surv(yearspan)~ south+mod, data=usa,random= ~ 1|group)
  What is the dimensionality of the covariates, e.g., are they factors with 
hundreds of levels?  How many unique levels are in the group variable?
The error message is surprising, as it appears to be coming from  conversion of
a sparse matrix to dense form.  The vector of frequencies for group might also
be useful.

	Terry Therneau