turn on suggestions

Auto-suggest helps you quickly narrow down your search results by suggesting possible matches as you type.

Showing results for

- JMP User Community
- :
- Discussions
- :
- Discussions
- :
- Sample sizing for future tolerance intervals

Topic Options

- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Get Direct Link
- Email to a Friend
- Report Inappropriate Content

Sep 22, 2014 7:50 AM
(4970 views)

Is there a way to determine the appropriate sample size for a future tolerance interval, given some historical data?

In essence, I will gather data and construct a tolerance interval (one- or two-sided) from this new data and compare the tolerance bound(s) to a specification limit. I need the tolerance bounds to be within the spec limit. I would like to be able to use the information from a prior sample to inform the minimum sample size.

I've written a simulation that I believe gives me the appropriate power that a given sample size will have a tolerance interval within my limits, but is there a formal way to approach this problem? Is there a formula somewhere that uses prior estimates/errors of the mean and standard deviation to inform a future tolerance interval sample size? Equivalently, are there formulas for power sample size calculations for percentiles?

Thanks!

Charles

1 ACCEPTED SOLUTION

Accepted Solutions

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Get Direct Link
- Email to a Friend
- Report Inappropriate Content

Apr 14, 2016 11:02 AM
(7689 views)
| Posted in reply to message from charlesgordon 09/22/2014 10:50 AM

I recently co-authored a paper in Quality Engineering titled "Sample size determination strategies for normal tolerance intervals using historical data" that provides a solution to this problem by calculating values to be used in the Faulkenberry-Weeks approach. It does not guarantee certain coverage levels but it did perform very well in numerical studies. The norm.ss formula is available in the R package 'tolerance'.

http://www.tandfonline.com/doi/full/10.1080/08982112.2015.1124279

3 REPLIES

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Get Direct Link
- Email to a Friend
- Report Inappropriate Content

Sep 22, 2014 3:28 PM
(4360 views)
| Posted in reply to message from charlesgordon 09/22/2014 10:50 AM

7.2.6.4. Tolerance intervals based on the largest and smallest observations

The NIST/SEMATECH e-Handbook of stats methods is a great (free) on-line resource for starting to answer such questions (NIST/SEMATECH e-Handbook of Statistical Methods). I have provided the link the to one of the sections on tolerance intervals. On that page is a link to the Hahn and Meeker book on statistical intervals in which you will find details on many types of statistical intervals, parametric and non-parametric solutions, including sample size calculations.

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Get Direct Link
- Email to a Friend
- Report Inappropriate Content

Thank you, Karen. The links are very helpful and certainly relevant. I do not believe, however, that they specifically inform the sample size of a future tolerance interval based on historical data for a power calculation. Maybe my problem is unique.

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Get Direct Link
- Email to a Friend
- Report Inappropriate Content

Apr 14, 2016 11:02 AM
(7690 views)
| Posted in reply to message from charlesgordon 09/22/2014 10:50 AM

I recently co-authored a paper in Quality Engineering titled "Sample size determination strategies for normal tolerance intervals using historical data" that provides a solution to this problem by calculating values to be used in the Faulkenberry-Weeks approach. It does not guarantee certain coverage levels but it did perform very well in numerical studies. The norm.ss formula is available in the R package 'tolerance'.

http://www.tandfonline.com/doi/full/10.1080/08982112.2015.1124279