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Created:
May 24, 2019 9:06 AM
| Last Modified: May 24, 2019 9:14 AM
(2081 views)

In the book “Optimal Design of Experiments: A Case Study Approach”, 1st Edition, by Peter Goos, and Bradley Jones Chap 9, the following text appears (Note that Brad Jones, @bradleyjones, is the Principal Research Fellow in the JMP division of SAS):

[Marc, looking at Brad] Why are you concerned about the response?

[Brad] Well, the type of response you have determines the kind of model you fit to the data. If your response were binary—for instance whether or not you have good adhesion—then a linear model would not be appropriate. Instead you'd need a logistic regression model, **and the experimental design you need for such a model is different from the one that is required for the linear models we usually work with**. If your response were an ordered categorical one—for instance, whether there is no, poor, good, or perfect adhesion—**then you'd need an experimental design for yet another model, the cumulative logit model**.”

This is just an aside in the book and there is no further detail.

So my question is, how do you do a DOE in JMP for Binary and Ordered Categorical Responses?

Thanks,

Larry

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Have you checked out non-linear DOE:http://www.jmp.com/support/help/14-2/nonlinear-designs.shtml

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Have you checked out non-linear DOE:http://www.jmp.com/support/help/14-2/nonlinear-designs.shtml

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Re: Binary and Ordered Categorical Responses Require a different kind of DOE?

I did not see that, thanks!

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