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  • JMP Security Notice: CVE-2026-109618 and CVE-2026-109619

    JMP promptly initiated a review of its products, services, and relevant infrastructure for exposure to CVE-2026-109618 and CVE-2026-109619.

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Paired t-test in Fit Y by X Platform with Unbalanced Data

We teach many of our engineers about paired t-tests and use the Fit Y by X platform (rather than Matched Pairs) when the format of their data set is more suitable for Fit Y by X. There are 2 frustrating aspects:

 

  1. There is still an option for 't test' in the analysis, which does an ordinary two-sample t-test, which ignores the Block that you incorporated. Most engineers/scientists don't realize this.
  2. If the data is unbalanced by even 1 data point (e.g. I have 20 pairs, but there is 1 missing data point or outlier that was discarded), you get an error message saying the Blocking is going to be ignored. It's a somewhat confusing message for them, and I feel that most engineers/scientists just blindly keep following the platform output. If I had fit the same model using Fit Model, this slight unbalance in the data can easily be utilized to give the correct hypothesis testing output. I'd like to see the Fit Y by X output handle the unbalanced data when the correct model is rather straightforward.
2 Comments
Jeff_Perkinson
Community Manager
Status changed to: Yes, Stay Tuned!

We are working on this for JMP 16.

Jeff_Perkinson
Community Manager
Status changed to: Delivered

In JMP 16 when a Block variable is specified and the cell counts are unequal, the Oneway report contains Fit Model Standard Least Squares output to accommodate the blocking.