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
- :
- Calculating Sample Size for Non-normal ordinal data

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

May 15, 2014 1:19 PM
(1121 views)

I am trying to calculate the sample size required to assess a process improvement that is expected to reduce the proportion of high values of a final measurement by 15% to 30%. I would like to know the number of samples required such that the process improvement compared to historical results is detected with various levels of confidence (e.g., 90%, 95%, etc.). The historical data distribution I am working with is not continuous data (ordinal) and is not normally distributed. A distribution showing sample data is attached.

Can anyone help me with this? Thanks.

2 REPLIES

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

If you have a known historical distribution I suggest doing it via a simulation. Unfortunately, I have no idea of how to do that in JMP

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

One approach would be to treat the data as binomial, high and not high. Then you're looking for a binomial sample size which should be moderately easy, but like Reeza I don't know how to do that in JMP.