[R-sig-ME] Specifying a repeated-measure design with 3 fully crossed within-subject factors

[Michael Cone]

Dear list,

I'm trying to specify the appropriate random effects structure for a 
repeated-measure design with multiple, fully crossed within-subject 
factors.

F1, F2 & F3 are fully crossed factors, repeated several times (> 100, 
but not fully balanced) for each subject (each subject saw each unique 
combination of F1xF2xF3 several times, order not important). Subjects 
are nested within sex. F1 has 4 levels, F2 10 levels, and F3 40 levels.

I am interested in F1, F2, F3 and sex as fixed factors, but trying to 
account for the massive amount of pseudo-replication within the data 
set.

I tried to do my homework, and, for a simple repeated measure on 
different subjects characterized by sex, something like
meas ~ 1 + (1 | sex/subject)
would be appropriate. I am having a hard time, though, extending this 
to my design, where a repeated measure on a few subjects was repeated 
for each combination of factors F1, F2, and F3. Is it simply
meas ~ 1  + (1 | sex/subject) + (1 | F1) + (1 | F2) + (1 | F3)?

I apologize if this is something obvious. I'm new to mixed models & 
lmer and wasn't able to find a similar enough example despite quite some 
perusing.

Many thanks,
Michael