[R] Regarding aov Error()

[John Vokey]

The following dummy data frame has factor Q (with 2 levels) nesting  
factor P (with levels p1 and p2 nested under q1, and p3 and p4 nested  
under q2), but both crossing the random variate s, which has 8  
levels.  The dependent measure is dv.
 > # The data frame:
 > testnest
    dv  s  P  Q
1   1 s1 p1 q1
2   2 s2 p1 q1
3   1 s3 p1 q1
4   2 s4 p1 q1
5   1 s5 p1 q1
6   3 s6 p1 q1
7   3 s7 p1 q1
8   4 s8 p1 q1
9   2 s1 p2 q1
10  3 s2 p2 q1
11  3 s3 p2 q1
12  1 s4 p2 q1
13  1 s5 p2 q1
14  2 s6 p2 q1
15  2 s7 p2 q1
16  3 s8 p2 q1
17  3 s1 p3 q2
18  3 s2 p3 q2
19  4 s3 p3 q2
20  1 s4 p3 q2
21  1 s5 p3 q2
22  1 s6 p3 q2
23  2 s7 p3 q2
24  2 s8 p3 q2
25  4 s1 p4 q2
26  3 s2 p4 q2
27  1 s3 p4 q2
28  2 s4 p4 q2
29  4 s5 p4 q2
30  1 s6 p4 q2
31  3 s7 p4 q2
32  1 s8 p4 q2

# The following aov() call is structurally correct with respect
# to the design, and appropriate error-terms, but, as can be seen,
# returns an error:

 > testnest.aov=aov(dv~Q+P%in%Q+Error(s+s:Q+s:P:Q),data=testnest)
Warning message:
Error() model is singular in: aov(dv ~ Q + P %in% Q + Error(s + s:Q +  
s:P:Q), data = testnest)

# However, applying the summary() method to the aov output, produces  
the correct analysis:

 > summary(testnest.aov)

Error: s
           Df Sum Sq Mean Sq F value Pr(>F)
Residuals  7 5.8750  0.8393

Error: s:Q
           Df  Sum Sq Mean Sq F value Pr(>F)
Q          1  0.1250  0.1250   0.068 0.8018
Residuals  7 12.8750  1.8393

Error: s:Q:P
           Df Sum Sq Mean Sq F value Pr(>F)
Q:P        2  0.250   0.125  0.1111 0.8956
Residuals 14 15.750   1.125

I have tried many different ways of denoting the Error()  
partitioning, but can't find one that produces both the correct  
analysis *AND* no singularity error on the aov() call.  Any suggestions?

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-Dr. John R. Vokey