[R] glmer (lme4), glmmPQL (MASS) and xtmepoisson (Stata)

[Antonio.Gasparrini at lshtm.ac.uk]

Dear R users,
 
I'm trying to specify a generalized linear mixed model in R, basically a Poisson model to describe monthly series of counts in different regions.
My aim is to fit subject-specific curves, modelling a non-linear trend for each region through random effects for linear splines components (see Durban et al,  Stat Med 2005, or " Semiparametric regression" by Ruppert et al, 2003).
 
I use the command 'glmmPQL' in the MASS package and replicated the analysis with Stata's 'xtmepoisson'.
I obtained very different results, so I would like to try 'glmer' in the lme4 package.
I guess the default correlation for the random effects in  'glmer' is unstructured, but this choice is absolutely unfeasible for this complex random effect nesting structure.
Unfortunately, I couldn't find a way to input simpler correlation structures (namely diagonal or identity), in the same way as the using the functions pdDiag or pdIdent with 'glmmPQL'.
 
I wonder if this option is still to be implemented in lme4.
In this case, any suggestion/comment?
 
Thanks for your time

Antonio Gasparrini
Public and Environmental Health Research Unit (PEHRU)
London School of Hygiene & Tropical Medicine
Keppel Street, London WC1E 7HT, UK
Office: 0044 (0)20 79272406 - Mobile: 0044 (0)79 64925523
Skype contact: a.gasparrini
http://www.lshtm.ac.uk/people/gasparrini.antonio ( http://www.lshtm.ac.uk/pehru/ )