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May 16, 2013 1:21 PM
(3247 views)

Hello,

I am dealing with 3 continuous independent variables (e.g. D,E,F) and 1 continuous dependent variable (e.g. X).

Some time (~1 year) ago, I was able to use JMP to generate a mathematical model of the form "X = c*D*E*F", where c is just a dimensionless constant. Presently, however, I am having trouble replicating that process in JMP 10; the 'closest' I have gotten so far by playing around with the "Fit Model" settings is "X = (D-d)(E-e)(F-f)", which is still quite different.

If anyone could help by directing me towards the correct method for generating a model of the form "X = c*D*E*F", I would greatly appreciate it.

Thanks!

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May 17, 2013 1:53 PM
(5062 views)
| Posted in reply to message from pamplemousse 05/16/2013 04:21 PM

Not sure why you would want to do this but in order to obtain what you are requesting once could use the Fit Model platform and specify X as your response and the 3 way interaction D*E*F as the modeling term. Then check the no intercept button and under the red triangle deselect center polynomials and you will obtain what you are looking for.

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May 17, 2013 1:53 PM
(5063 views)
| Posted in reply to message from pamplemousse 05/16/2013 04:21 PM

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Re: Question regarding modeling in JMP 10

Thanks a lot! Forgetting to deselect "center polynomials" was my sole impediment.

While waiting for a reply, I constructed a new column for the product "(D*E*F)" and performed a linear regression of the form X = c(D*E*F), yielding the same regression coefficient ("c") as my preferred method.

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Re: Question regarding modeling in JMP 10

May 17, 2013 2:11 PM
(3037 views)
| Posted in reply to message from pamplemousse 05/16/2013 04:21 PM

One way to do your regression is as follows: Create a new column in your table with formula c*D*E*F where c is a new parameter (created by adding c to the list of formula parameters).with some initial value. Then use the **nonlinear platform** to do the regression using X as the dependent variable and the new column as the X formula.

PG