[R] significant anova but no distinct groups ?

[Frederic Jean]

Dear all,

I am studying a dataset using the aov() function.

The independant variable 'cds' is a factor() with 8 levels and here is  
the result in studying the dependant variable 'rta' with aov() :

> summary(aov(rta ~ cds))
             Df  Sum Sq Mean Sq F value  Pr(>F)
cds          7 0.34713 0.04959  2.3807 0.02777
Residuals   92 1.91635 0.02083

The dependant variable 'rta' is normally distributed and variances are  
homogeneous.
But when studying the result with TukeyHSD, no differences in 'rta'  
are seen among groups of 'cds' :

> TukeyHSD(aov(rta ~ cds), which="cds")
   Tukey multiple comparisons of means
     95% family-wise confidence level

Fit: aov(formula = rta ~ cds)

$cds
              diff        lwr        upr     p adj
1-0 -0.1046092796 -0.4331100 0.22389141 0.9751178
2-0  0.0359991860 -0.1371359 0.20913425 0.9980970
3-0  0.0261665235 -0.1348524 0.18718540 0.9996165
4-0  0.0004502442 -0.1805448 0.18144531 1.0000000
5-0 -0.1438949939 -0.3104752 0.02268526 0.1422670
[...]
7-5  0.0621598639 -0.1027595 0.22707926 0.9386170
7-6  0.0256519274 -0.1757408 0.22704465 0.9999248

I tried a pairwise.t.test (holm correction) which also was not able to  
detect differences in 'rta' among groups of 'cds'
I've never been confronted to such a situation before : is it just a  
problem of power of the /a posteriori/ tests used ? Do I miss  
something important in basic stats or in R ?
How to highlight differences among 'cds' groups seen with aov() ?

Any help appreciated
Thanks in advance,

Fred J.