Hi @DrThWillms,
There are many ways to create a model in JMP, especially if you are using a Definitive Screening design.
You can use The Fit Definitive Screening Platform, The Fit Two Level Screening Platform (even if you have 3 levels, it can include quadratic effects in the effects testing), Fit Least Squares (JMP) and Generalized Regression Models (JMP Pro) throught the Fit Model platform, ... not to mention other modeling strategies like Machine Learning and the associated algorithms.
I don't understand your point :
@DrThWillms wrote:
However, I would have liked the spontaneous evaluation as present in the moment
where I entered all data. Is this possible?
It seems to be very tedious to create the model by the given option.
What are your difficulties ?
Is it a problem of defining the effects to be tested ? The Fit Definitive Screening lacks the flexibility of the Fit Model platform where you can specify the terms to be tested in the model. It will by default test all main effects, 2-factors interactions, and quadratic effects, following a sequential approach : it first select and fit main effects, and in a second step it will select and fit second order effects (2-factors interactions and quadratic effects) based on effect heredity. More infos about this 2-stage approach here : Statistical Details for the Fit Definitive Screening Platform
I would recommend try fitting models in different ways/ with different platforms, to better understand where they agree and disagree. Then, based on statistical evaluation and domain expertise, you can select and/or combine the most relevant model(s) and run validation points to confirm the relevance and accuracy of your model.
Hope this answer may help you or contribute to the discussion,
Victor GUILLER
L'Oréal Data & Analytics
"It is not unusual for a well-designed experiment to analyze itself" (Box, Hunter and Hunter)