User Community
cancel
Turn on suggestions
Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.
Showing results for 
Show  only  | Search instead for 
Did you mean: 
  • Learn how to build custom Python data connectors and further customize JMP’s Data Connector Framework with the Python Data Connector Demo, available now in the JMP Marketplace!
  • See how to move from signal modeling to system modeling at the first JMP Aerospace Analytics webinar. Register. June 18, 1 p.m. US Eastern Time.

JMP Wish List

We want to hear your ideas for improving JMP. Share them here.
Choose Language Hide Translation Bar

Missing value handling for Ordinal variables in Partition

Status: Archived Submitted by on ‎09-20-2018 04:57 PM
2 Comments (2 New)

Suggestion:  Please treat missing data (and missing value code data) for ordinal X/Factor variables the same as continuous X/Factor variables when the informative missing option is selected.  That is, test to see if missing is better grouped "high" or "low".  Right now, it appears to be treat the missing value (or missing value code) as an ordinal value and assign it accordingly. 

2 Comments
Ryan_Gilmore
Community Manager Community Manager
Community Manager
‎10-26-2022 04:34 PM
‎10-26-2022 04:34 PM
Status changed to: Archived
We are archiving this request. If this is still important please comment with additional details and we will reopen. Thank you!
hengehold_da1
Level III
‎11-08-2022 01:33 PM
‎11-08-2022 01:33 PM

It appears to work in JMP 16 when the dependent variable is continuous, but when the dependent variable is ordinal, it appears to just put the missing value category of the ordinal predictor variable with the low category group in the split.  So, I think this is still an open ask.