[R] lmer with 2 random effects with only two levels

[gmd]

Dear all,

I am analysing a data set based on 6 groups of individuals.   Each group is
observed for 10 days. 5 days with one manipulation 5 days with another
manipulation. I therefore have 6 replicate groups (n=6) each with one mean
measurement for manipulation A and manipulation B.  Each group consists of a
set of males and females. An independent group of males for each group
replicate, however there are only 2 sets of females each replicated 3 times
within the six groups.  

data takes the from:

group      response     female set   treatment
 
1               3.0                 A           high
2               3.0                 B          high
3               2.8                 A           high
4               2.6                B             high
5               2.6                 A            high
6               2.9                B              high
1               1.5                A              low
2               1.4               B                low
3               1.7              A               low
4               1.9              B               low
5               2.0              A               low
6                2.1              B              low

The order of treatment is counterbalanced and I would assume I would choose
to fit the model:

> model1<-lme(response~treat, random=~1|femaleset/group)

or
> model2<-lmer(response~treat+(1|femaleset/group))

However I am concerned with two aspcts:  my small sample size of course but
also the use of a random effect of female set only has two levels (A and B).

Is there a more appropriate way to handle this analysis?  A glm with female
group as an explanatory for instance such as:

model3<-glm(response~treatment+femaleset+treatment*femaleset).  Although
yhis will not properly account for the pseudoreplication.  Ant assistance or
help would be greatly appreciated.

Best 
Colin


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