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May 21, 2014

JMP 13 Preview: Making definitive screening designs more accessible

The purpose of screening in designed experiments is “to separate the vital few factors that have a substantial effect on the response from the trivial many that have negligible effects….The definitive screening design can reliably accomplish the task of screening even if there are a couple of second-order effects,” wrote Bradley Jones, JMP Research Fellow, in a blog post introducing definitive screening designs (DSDs) in 2012.

After DSDs became available in JMP 11, the response from users was swift and uniform. “I’m amazed by how quickly these designs have been accepted for routine use by the community of practitioners,” says Bradley, co-inventor of DSDs.

Why do people like DSDs? “They have a lot of properties that are desirable compared to other screening designs. Typically, you start with a screening design and then fit a higher-order model. With DSDs, you can sometimes skip that second step,” he explains.

Fit definitive screening design (left) with follow-up reduced model (right) run from this new platform. Fit Definitive Screening design (left) with follow-up reduced model (right) run from this new platform in JMP 13.


Now in JMP 13, released later this month, users have a more robust way to statistically model DSDs, with an option to Fit Definitive Screening available in the DOE menu.

What does this mean? JMP now includes a complete end-to-end workflow for building and fitting DSDs, making it easier for scientists and engineers to try them out for their own work. The table generated by the definitive screening design automatically includes a script to fit the design with the new platform.

This platforms aids in finding second-order effects and quadratic effects, if they exist, with a fitting procedure that takes advantage of the structure of a DSD to provide more clear-cut results than generic model selection tools can provide. Ultimately, this new option in DOE means that people who have limited statistics expertise can be successful in finding real causal effects.

“I believe DOE is the most beneficial thing statistics has provided to people in science and engineering because practically any system, product or process can be improved by employing DOE. That’s the reason I’ve dedicated my professional life to working on DOE. I want to lower the barrier of accessibility for engineers and scientists to use it, so they don’t have to be an expert or have a professional statistician available at their elbow,” says Bradley.

While he is hopeful that more JMP users will try definitive screening designs in JMP 13, he cautions that the design is not for every situation they may encounter. Refer to his blog post about “Proper and improper uses of definitive screening designs” for details.

To learn more about what’s coming in JMP 13, stop by the preview page on our website. There, you can sign up to watch a live stream of JMP chief architect John Sall’s tour of JMP 13 on Sept. 21, as well as watch short videos about JMP 13 and JMP Pro 13.