What inspired this wish list request? Please describe the current issue that needs improvement or the problem to be solved that is not easy or possible right now, with an example use case.
Mixed models are widely used in our day-to-day work e.g. to accommodate for potential block effects of multiple workpackages. When analyzing obtained data there is no way of performing model selection considering the prevalence of these random effects. Other software providers have implemented this feature already especially mentioning Design-Expert (Design-Expert | Stat-Ease) and also recently Effex (Design of Experiments
software - Data Analysis, Stat & Process Improvement) with their latest update: "A unique all-subsets tool for model selection in the presence of random effects! "
What is the improvement you would like to see?
I want JMP to introduce model selection for mixed models.
Why is this idea important?
Mixed models are widely used in countless areas. Being able to directly perform model selection with random effects in JMP would greatly improve JMP's functionalities and benefit all users working with mixed models. Additionally, it would keep JMP competitive in its mixed model functionalities to its competitors.