[R] extracting nested variances from lme4 model

[Frank Samuelson]

I have a model:
mod1<-lmer( x ~  (1|rtr)+ trth/(1|cs) , data=dtf)  #

Here, cs and rtr are crossed random effects.
cs 1-5 are of type TRUE, cs 6-10 are of type FALSE,
so cs is nested in trth, which is fixed.
So for cs I should get a fit for 1-5 and 6-10.

This appears to be the case from the random effects:
 > mean( ranef(mod1)$cs[[1]][1:5] )
[1] -2.498002e-16
 > var( ranef(mod1)$cs[[1]][1:5] )
[1] 23.53083
 > mean( ranef(mod1)$cs[[1]][6:10] )
[1] 2.706169e-16
 > var( ranef(mod1)$cs[[1]][6:10] )
[1] 1.001065

However VarCorr(mod1) gives me only
a single variance estimate for the cases.
How do I get the other variance estimate?

Thanks for any help.

-Frank



My fake data set:
-------------------------------------------
data:
$frame
              x rtr  trth cs
1   -4.4964808   1  TRUE  1
2   -0.6297254   1  TRUE  2
3    1.8062857   1  TRUE  3
4    2.7273275   1  TRUE  4
5   -0.6297254   1  TRUE  5
6   -1.3331767   1 FALSE  6
7   -0.3055796   1 FALSE  7
8    1.3331767   1 FALSE  8
9    0.1574314   1 FALSE  9
10  -0.1574314   1 FALSE 10
11  -3.0958803   2  TRUE  1
12  12.4601615   2  TRUE  2
13  -5.2363532   2  TRUE  3
14   1.5419810   2  TRUE  4
15   7.7071005   2  TRUE  5
16  -0.3854953   2 FALSE  6
17   0.7673098   2 FALSE  7
18   2.9485984   2 FALSE  8
19   0.3854953   2 FALSE  9
20  -0.3716558   2 FALSE 10
21  -6.4139940   3  TRUE  1
22  -3.8162344   3  TRUE  2
23 -11.0518554   3  TRUE  3
24   2.7462631   3  TRUE  4
25  16.2543990   3  TRUE  5
26  -1.7353668   3 FALSE  6
27   1.3521369   3 FALSE  7
28   1.3521369   3 FALSE  8
29   0.2054067   3 FALSE  9
30  -1.7446691   3 FALSE 10
31  -6.7468356   4  TRUE  1
32 -11.3228243   4  TRUE  2
33 -18.0088554   4  TRUE  3
34   4.6264891   4  TRUE  4
35   9.2973991   4  TRUE  5
36  -4.1122576   4 FALSE  6
37  -0.5091994   4 FALSE  7
38   1.2787085   4 FALSE  8
39  -1.6867089   4 FALSE  9
40  -0.5091994   4 FALSE 10