Hi all,

I'm new to mixed models and lme4 and would appreciate any help on  
specifying models in lme4. Specifically I'm wondering about  
specifying nested variables. As I understand it lmer is capable of  
determining the nesting structure by itself (as long as the nesting  
is not implicit in the factors), so is there ever a need for  
specifying the nesting structure in the model specification when  
using lmer? Assuming A and B are random factors, B is nested in A,  
and Y is a response. What would be the difference between the  
following model specifications?

(i)	lmer(Y ~ (1|A) + (1|B))
(ii)	lmer(Y ~ (1|A) + (1|A:B))
(iii)	lmer(Y ~ (1|A) + (1|A/B))

On a different note: using the mcmcsamp method, is it possible to  
change the choice of priors? I understand that this is a longshot and  
that it is most likely not possible, but I'm still asking just to be  
sure. Is there another way this can be done (i.e. sampling from the  
posterior distribution of a mixed model but with a general choice of  
prior)?

Thank you very much!

Best regards,

Martin.

========================================
Martin Eklund
PhD Student
Department of Pharmaceutical Biosciences
Uppsala University, Sweden
Ph: +46-18-4714281
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