[R] estimating treatment effect in blocked experiment

[Mark A. Albins]

R-help,

I am interested in estimating the effect of a treatment (2 levels) on a 
response.  I've used a randomized blocked experiment (5 blocks).  I run 
the full model, let's say that it is...

lm1 <- lm(resp ~ treat + block)

...and find that there are no significant block effects.  Now with 
"treatment" contrasts, the parameter estimate for the non-reference 
treatment group can be interpreted as the mean treatment effect 
(difference in mean response between the two treatments) in the 
reference block only.  Is that correct?

I know that this mean is not significantly different from the mean 
effect in the other four non-reference blocks (because the block effect 
was not significant), but I also know that the mean effect of the 
treatment across all blocks is not equal to the mean in the reference 
block.  In other words, if I run the model without the blocking factor...

lm2 <- lm(resp ~ treat)

I'll get a slightly different effect size, and a different (larger) 
estimate of the uncertainty about that effect.

What I really want is the effect size estimate from the second model, 
with an estimate of uncertainty for that effect from the first model. Is 
that correct?

Is this a situation in which one might modify the contrast matrix for 
the block factor?  Can you keep block in the model but estimate the 
parameter of interest averaged across all blocks?

Any help or clarification on this issue would be appreciated.

Thanks,

Mark