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Definitive Screening Design Categorical Factor Levels

chris_dennis

I am working on a Definitive screening Design (my first) I set design up with 7 factors one of which was a categorical (equipment type) with two levels. When reviewing design with team, request was made to skip step for this equipment two set one of the continous factors to 0.

I am reviewing design now and this change really makes the categorical variable into a 3 level item. I am concerns about issues this may cause with results analysis, and if there are any special steps I should take to modify the design to handle this item?

Any help or suggestions are appriceated.

Thanks, Chris

Accepted answers

Phil_Kay

Okay.
I had a quick look at the consequence of adding the 3rd level to your categorical X1 when X2 = 0. It does have some significant effects on the properties of your design, as you might expect. I would encourage you to have a look for yourself using the Design Evaluation platform.
Also, I am not sure that it really helps with interpretation of the resulting model. Your resulting model would cover possibilities where X1 = L3 (i.e. no machine used) and X2 > 0, which doesn't make a lot of sense.
You could just keep the design as is and not worry that X1 is essentially meaningless when X2 = 0. The term for the interaction of X1 and X2 should be able to capture the fact that there is no difference between levels of X1 when X2=0.
Or you could reframe the problem or rethink factor ranges so that they make more sense.
Or you could go to a Custom Design.
I hope this helps.
Cheers,
Phil

All comments

Phil_Kay

Hi Chris,

I am not quite sure what you mean. Could you send the design. If necessary you could create an anonymised version jsut with X1... X7 and coded factor levels (-1,0,1).

Regards,

Phil

chris_dennis

Please see attached design example.

[cid:image001.png@01D32B9C.310881D0]

Jeff_Perkinson

Unfortunately, images in email replies don't make it to the Community. @chris_dennis, could you edit your response above to attach the image?

chris_dennis

Example of design shown below. Concern is the Catagorial factor (X1) is the tool used for parameter X2. If X2 is 0 then it does not run on tool for X1 and skips this step. I think this have the effected of making X1 three categories; L1, L2 and None. Is the design still valid under this condition? See attached PDF for design.

Design example.pdf

Phil_Kay

That is interesting. So you have a categorical X1 (L1, L2) and a continuous X2 (0, 8000, 16000). And if X2 is 0, then X1 is neither L1 nor L2.

Does it make sense to define X2 as a continous over the range 0 to 16000? After you have run the experiment and modelled the data, will it make sense for the model to make predictions of the response for X2 = 1 or X2 = 500? Would you actually operate in the range 1 to 8000?

Could you change X2 to have a range of 1 to 16000? Or some other range with a lowest setting > 0.