[R-sig-ME] lmer vs glmmPQL

Federico Calboli f.calboli at imperial.ac.uk
Wed Jun 24 11:45:46 CEST 2009


On 23 Jun 2009, at 22:46, Ken Beath wrote:
>
> This seems to results from the use of a t-test with few df in glmmPQL
> and z in lmer. z seems fine to me. What is more of a problem is that
> your random effects variance is effectively 0. There are only 3 blocks
> so fitting a random effects model will be difficult and appears
> unnecessary.


That was a sample dataset so I could see what kind of data I had to  
deal with, the 'real' hing should have a variance > 0 for the random  
effect. My philosphycal issue was, given such a relatively  
straightforward model, should I be more (glmmPQL) or less (lmer)  
conservative?

Best,

Federico

--
Federico C. F. Calboli
Department of Epidemiology and Public Health
Imperial College, St. Mary's Campus
Norfolk Place, London W2 1PG

Tel +44 (0)20 75941602   Fax +44 (0)20 75943193

f.calboli [.a.t] imperial.ac.uk
f.calboli [.a.t] gmail.com




More information about the R-sig-mixed-models mailing list