This website uses Cookies. Click Accept to agree to our website's cookie use as described in our Privacy Policy. Click Preferences to customize your cookie settings.
Accept
Reject
Preferences
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: 
Have your say in shaping JMP's future by participating in the new JMP Wish List Prioritization Survey

Practice JMP using these webinar videos and resources. We hold live Mastering JMP Zoom webinars with Q&A most Fridays at 2 pm US Eastern Time. See the list and register. Local-language live Zoom webinars occur in the UK, Western Europe and Asia. See your country jmp.com/mastering site.

Choose Language Hide Translation Bar
Developer Tutorial: Designing and Evaluating Measurement Systems Studies Prior to Implementation
Created: Oct 28, 2022 04:27 PM  |  Last Modified: Oct 24, 2023 02:21 PM
MSA_Tech_Tutorial_Files.zip

(view in My Videos)

 

Note: All the capabilities shown are in JMP 17, althogh JMP Pro 17 is used for the demo.  The video includes Q&A and comments from the presenter Caleb King @calking about how MSA works plus plans for possible enhacements. 

 

See how to:

  • Understand basics of MSA Design

    • MSA primary focus is on decomposing variation in product measurements into distinct sources, with the goal to reduce or elimnate one or more sources

    • The metric of interest is not an effect size (i.e. difference in mean behavior), but rather the variance contribution from a particular source

    • Underlying models are primarily random effects models or even mixed effects models if biasing terms are included

    • Nested factors are also common in MSA, but not exclusively 

  • See improvements made in JMP 17

    • Better diagnostics that more closely align with MSA analytics platforms

    • Greater user interaction that allows exploration of what-if scenarios

    • Fexible Design structure interface so  users can specify nesting/crossing relationships in the design

  • Understand that diagnostics are based on simulation of variance estimates, based on the standard ANOVA approach

    • Example is a 3- factor fully crossed MSA where mean squares have known Chi-square distributions that are easily be simulated and then used to compute confidence intervals, variance proportions, etc.

  • Include nested and crossed structures
  • Make design and evaluate diagnostics for two examples

MSA Design Factor ScreenMSA Design Factor Screen

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

The video includes Questions ansered at the webinar by Caleb @calking, Don McCormack @DonMcCormack and Jerry Fish @JerryFish.

 

One person asked online if nesting would occur when testing same methods on different equipment.  They responded: Probably not, but it would ultimately depend on how the experiment was run what assumptions were made about the methods and equipment.  If you considered the equipment/method to be a random observation from a much larger population, then they may be considered nested (in some way). If you considered them from a fixed set of values (e.g., types of equipment), then they would more likely be treated as crossed.

 

 

Resources

0 Kudos

Recommended Articles