Possible linking between FDE profiler and mixture profiler

Victor_G

Hello dear JMP-users,

I have a question regarding the use of FDE profiler and mixture profiler.

I have two DoE datatables, one with summarized tests results from a mixture design with 3 components (giving me only one value for the response), and the other one with complete tests results from the same DoE (with signal curves as test response).

 

Problem : When I use the DoE-FDE profiler to look at the changes in the curve, I struggle to look at the different possibilities of mixtures, as changing one component quantity will automatically change other components quantities. This is normal because of the mixture design (and dependancy of the mixture factors), but I have troubles to have a curve for a mixture at X1 = 0,6 ; X2 = 0,3 and X3 = 0,1 for example, because when I change X1 to 0,6 JMP change automatically quantities of X2 and X3 at 0,2.

 

Is it possible to link the mixture profiler from the summarized datatable (triangle) with the DoE-FDE profiler ? In order to point specific mixtures in the triangle/mixture profiler and look at the corresponding curves in the FDE profiler ?

Thanks in advance for your help ! 

Victor G.

Mark_Bailey

That's good - the latest version includes a lot of enhancements to make what you want to do very easy!

 

Unfortunately, the Mixture Profiler does not work with functional data models. You can still use other profilers, though, such as the Prediction Profiler. In case that approach is useful but you are not familiar with the steps involved, follow these steps:

 

You must use the stacked column format to be able to put your design and the functions together. So one column for the functions, one column for the domain, and one column for the function identity. Add a column to the design data table that associates the experiment run (row) with the function ID. Then use Tables > Join to merge them by matching on the ID column in each data table.

 

Now select Analyze > Specialized Modeling > Functional Data Explorer. Use the default tab in the launch dialog box for stacked data. Assign the functions, domain, and ID as usual. Select the factor data columns and assign them to the Z, Supplementary role. The last step is key to making this analysis easy.

 

Fit your basis expansion model and select the number of FPCs that you want as before. Click the red triangle next to Function Summaries and select Save Summaries. This command produces a new data table. It automatically includes a table script to launch the Prediction Profiler.

 

I hope that this answer is helpful, even if you can't get the profiler that you want.