R help - Mar 2006 - optimal factorial designs

Hi All,

recently I used Design Expert for some Design Of Experiment work.
I was happy with the interface to select which effects I want to see in my
experiment, and which not.
For example: I can select of course my main effects, but also if I want to see
interaction A:B, B:C, A:B:C,but not A:C.

This was very interessting as you can end up with fewer runs, especially in
cases of 10 factors with 2-3 levels.

Is there a way to do this with R?
I found the AlgDesign package, and I tried optFederov and optMonteCarlo, as you
can set a formula (like: A+B+C+A:B+B:C+A:B:C). But while using this, I end up
with to much runs, so I have some residuals. And sometimes I cant get the right
interactions from my design.
So: are there better ways to achieve the right design?

Kind regards

Bart

	[[alternative HTML version deleted]]

From: Bart Joosen
> 
> Hi All,
> 
> recently I used Design Expert for some Design Of Experiment 
> work. I was happy with the interface to select which effects 
> I want to see in my experiment, and which not. For example: I 
> can select of course my main effects, but also if I want to 
> see interaction A:B, B:C, A:B:C,but not A:C.
Just out of curiosity, how do you make sense out of a model with A:B:C
interaction but not A:C?

Andy

 
> This was very interessting as you can end up with fewer runs, 
> especially in cases of 10 factors with 2-3 levels.
> 
> Is there a way to do this with R?
> I found the AlgDesign package, and I tried optFederov and 
> optMonteCarlo, as you can set a formula (like: 
> A+B+C+A:B+B:C+A:B:C). But while using this, I end up with to 
> much runs, so I have some residuals. And sometimes I cant get 
> the right interactions from my design.
> So: are there better ways to achieve the right design?
> 
> Kind regards
> 
> Bart
> 
> 	[[alternative HTML version deleted]]
> 
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