Different mixture experiment analysis results JMP 17 & 18

[#1]

Did something in JMP 18 change in analysis of mixture experiment results. Below is shown that analysis results from exactly the same DOE data sets are different

1. DOE three component mixture

JMP 17 results 

JMP 18 Results

2. DOE three mixture components + one process effect

JMP 17 results 

JMP 18 results 

In JMP 18 analysis above the model is different!

What has changed and why? Remark: despite of different plots & model graphs of JMP 17 - 18 prediction profilers are identical. 

[#2]

Hi @frankderuyck,

In the first case, can you provide anonymized dataset ? Are the columns properties the same ? 

In the second case, the models are different in the two captures. You should have similar results by having the same models.

[#3]

My first three component case study above was similar to the one presented in a known earlier JMP webcast vinegar/oil/water case study below, you can see that the plot is also similar to mine but not the same in JMP 18

[#4]

I remeber that the explanation for the wide confidence interval was the strong collinearity among the mixture effects which makes sense; this does not show up anymore in the JMP 18 plot (?)

[#5]

The link to the webinar is https://community.jmp.com/t5/JMP-Blog/Summer-DOE-Series-Mixture-DOE/ba-p/669012

I got green light to use this data set for my DOE training

[#6]

Hi @frankderuyck,

I would compare the outcomes of the first use case on something else than p-values, due to multicollinearity in mixture designs.

Again, without any dataset to test, it's difficult to help you since we have only a partial view at this comparison.

For the first use case, if the model are set up correctly and in the same way between JMP 17 and 18, try to look at the Parameter estimates (and standard deviations), at metrics focussed on predictivity and optimization (like RMSE) and residuals/diagnostic plots. 

Since you mentioned the Profiler has similar results between versions, I would guess that the differences you are seeing are mostly due to the use of Mixture designs instead of a calculation change between versions.

[#7]

 Find in attachment the DOE analysis data set

During my september training I still used JMP 17, trainees got JMP 18, it was a big surprise and annoying that my 17 training results were different! Mine are similar (same data) to those presented in webinar above, think also with JMP 17. 

[#8]

Strange, I used your data table and analyzed in both 17 and 18.  The only difference I found was the confidence limits on the Actual by Predicted  plots (leverage).  All of the other statistics were identical (I used your scripted fit model).

JMP18

JMP17

 

 

[#9]

Indeed question is why?

[#10]

The jmp 17 plot is should be more accurate because of the very strong collinearty among mixture components; limits from jmp 18 are to my opinion too narrow?