JMP Wish List

Is it possible to add an option to automatically obtain AICc (and BIC) in "Nonlinear" to the next JMP versions? This is a big weakness of recent version. ... View more

  The MaxDiff DOE tool currently generates a basic randomization.  However, it does not provide the important next step that sensory and consumer research practitioners require which is the expansion of the basic design  to be replicated for many test subjects and then to randomize the order blocks.   It seems this capability is already available in other DOE tools such as the Custom Design int the baked in routine called, "Design Generation".   The output should look exactly as it does in the JMP example file called, "Candy Survey" that is, without the raw data collected in the column titled "Choice".    The pain point for researchers is that to use the JMP tool as currently configured, one would have to take the individual design and manually seed it and then randomize many times.  Our tests often contain between 40 and 120 test subjects and sometimes more!  So the current configuration is not helpful.   Please consider bringing the "Data Generation" option into the MaxDiff DOE.        ... View more

Would be nice to have more flexible column properties for spec limits and control limits. Current column properties allow only one spec limit or control limit. But many SPC users will have changing control limits and spec limits over time. Currently Control Chart Builder can use a Phase column to separate calculated control limits. Saving to a table it will show the _LCL, _Mean, _UCL, etc. for each phase, with phase as an additional column. Could spec limits and control limits work in this manner? The ability to use a table to pull in the requirements, or save from Control Chart Builder to the Column and not just the table? See wish list requests for more flexible Value Ordering and Value Labels column properties that may interact with JMP tables. Not sure how it would work with all platforms, such as Process Screening. Currently have to write scripts to add changing control limits or spec limits to charts and other platforms. ... View more

I'm a little underwhelmed at times with the options available under the DOE --> Design Diagnostics --> Sample Size and Power menu. Two particular omissions seem noteworthy for what I do: 2 standard deviations Equivalence tests (one, two, paired samples) In some other threads I've seen some mention around the topics, but they are not in the wish list.   Here are some links to those threads: Sample Size and Power for Testing standard deviations  TOST Acceptance criteria and Sample Size  As a reference, Minitab does seem to provide these options. I've use proc power in SAS for these situations. ... View more

When you create a model using the DoE platorms there is the option to simulate responses prior to the table being made but when you run the model script you have generated the :Y response is included, this means you have to change the model to use the :Y simulated responses you have just generated.   The idea is that if you Simulate Responses during the generation of a model the ':Y Simulated' should be included into the model dialogue, not the ':Y'   David ... View more

Cause-and-Effect-Diagrams are often used to visually relate Responses to possible Factors of a process in a brainstorming session (in JMP: Analyze -> Quality and Process -> Diagram).   I propose to extend the Diagram Platform by a Transfer-Tool in order to feed Responses and Factors from the Diagram directly into the DOE Custom Design Platform. In the transfer protocol the user must define the Data/Modeling Type of Factors if they are controllable, uncontrolled, covariates or constants (with practical information what these mean, e.g. uncontrolled may be a logged room temperature, covariates might be specimen dimensions that are measured as is, and cannot be requested to meet a specific value. Typically, there will be many constants which are then carried along for documentation) if they can easily be changed (Split-Plot) if the relationship between a Factor and a Response is assumed linear, quadratic, polynomial, ... and what the -1/+1 levels are, respectively what the levels of nominal Factors are (and how many) which interactions shall be examined (cross-table with all 2-way interactions ticked by default, those unwanted can be unticked. Practical info what interactions are should be supplied) if certain level combinations don't work (constraints) additional free text info about Responses and Factors ...? On send to DOE Custom Design the information will be used to fill the respective fields, upon request responses and factors will be saved, and the assumed model will be constructed using the info provided (so users don't necessarily need to concern themselves with the technique of constructing models in JMP - although it's of course a good idea to know how this works).   General information on Responses and Factors, such as Units, Limits, Goals should be supplied in the Transfer-Tool, as well.   In my experience, although we use Cause-and-Effect-Diagrams a lot, we never use them in JMP, because the information in there is not transferrable. From other tools I can't transfer this info into JMP-DOE either, but in JMP there would be a chance to give the Cause-and-Effect-Diagram additional value. Much more of process development and management could take place in JMP itself.  ... View more

For Responses and Factors (where appropriate) I would like an extra field to specify the Units that Responses are measured in and Factors are set at. Like Lower/Upper Limit for Responses and Role or Changes for Factors the specified Units would be saved to the Column Properties for that column.   When deciding upon the Values for Factors to use in the DOE one automatically thinks about the Value's Units anyway and it would be easy to enter them here, whereas later on in the data table many people don't bother entering Units (one reason being that one has to go into each column's properties one by one unless all Units are identical, which is rarely the case). ... View more

1. Multiple-comparisons for nominal Y's (as for continuous Y's in Fit Y by X and in Fit Model). 2. Multi-way contingency tables for factorial layout of X's, and a nominal Y. 3. Contingency table: give proper titles to the last column and last row (e.g. "Y sub-total" and "X sub-total"). 4. Contingency table: when "Col%" is requested, it should be presented also in the "Y sub-total" column and when "Row%" is requested, it should be presented in the row of "X sub-total". ... View more