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

[Ben Bolker]

 <Antonio.Gasparrini <at> lshtm.ac.uk> writes:

> 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'.
> 

  1. I would suggest continuing this conversation on the
r-sig-mixed-models at lists.r-project.org , which is specialized
for this kind of question.

  2. I don't think that a specific replacements for pdDiag/pdIdent
are on their way any time soon, but you can 
get a diagonal structure for the random effects: see p. 16 of

 (broken URL so gmane doesn't complain about long lines ...)

http://lme4.r-forge.r-project.org/slides/
  2009-07-21-Seewiesen/5LongitudinalD.pdf
 
for an example.

  Ben Bolker