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
- :
- How to calculate scale estimate in GLS

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
- Permalink
- Email to a Friend
- Report Inappropriate Content

Sep 6, 2016 12:29 PM
(1893 views)

4 REPLIES

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Sep 7, 2016 10:18 AM
(1792 views)

GLM doesn't provide the scaled estimates. You could use the JMP formula editor to create the scaled factors and then run the GLM.

Scaling doesn't have to do with the distribution assumptions; by scaling it puts factors on an equal footing to enable the comparison of the estimated coefficients across different factors originally in different measurement units.

If you use JMP Pro, in its Generalized Regression,the parameter estimate report by default shows the results for both original and scaled factors. Note that GenReg uses a slightly different scaling method--it subtracts the mean and then is divided by the standard deviation where as in OLS after the mean is subtracted it is divided by range/2.

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Sep 7, 2016 12:34 PM
(1792 views)

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Sep 7, 2016 1:13 PM
(1792 views)

Currently there is a JMP Add-in for effect size from OLS modes Calculate Effect Sizes Add-in

Random effects model are not supported.

- Mark as New
- Bookmark
- Subscribe
- Subscribe to RSS Feed
- Permalink
- Email to a Friend
- Report Inappropriate Content

Sep 8, 2016 12:19 PM
(1792 views)