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
- :
- Two-way ANOVA 'error'

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

Jun 9, 2016 5:46 PM
(691 views)

5 REPLIES

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

Jun 9, 2016 7:13 PM
(584 views)

Not seeing the data table you are using makes it pretty tough to diagnose the issue. Can you attach a copy of the data table. If the data responses are confidential, you can make the response data random values. What is critical are the values of Effect A and Effect B.

Jim

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

Jun 12, 2016 11:56 AM
(584 views)

Hi Jim,

Thanks for the reply and sorry for the delay! I had to leave out column headings for 'security' reasons. Column 1 is the sample number (e.g. 76-9). Column 2 is Effect A (e.g. HN) and Column 3 is Effect B (e.g. Control). Effect A has 7 levels, Effect B has 4 levels. There are several response variables in the table. During the initial two-way ANOVA run, I used Column 11 (fourth from the right, e.g. 1.2 at the top). The problem seems to rest with the control level. By the way, there are 10 observations (or tested subsamples) of each replicate; for instance, there are 10 HN x Low x 4 replicates = 40. Ditto with Control.

I hope this makes sense. This is an interactive study where both treatments (A and B) were added to each exp. unit. Thanks in advance. -LH

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

Jun 10, 2016 8:57 AM
(584 views)

I interpret 'run a full factorial' to mean that your model has terms for the two main effects and the interaction effect. I interpret 'ignored controls' to mean that you do not see estimates for this level of your factor. The parameterization of the model for categorical factors in JMP is such that the last level (think JMP value ordering) is not reported because it is equal to the negative of the sum of the estimates of the other levels. That is, all of the estimates must sum to zero.

Click the red triangle at the top next to Fit Least Squares and select Estimates > Expanded Estimates to see the results for the last level.

Learn it once, use it forever!

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

Jun 12, 2016 12:00 PM
(584 views)

Hi Mark,

Thanks for the reply and sorry for the delay! (This is the same message to Jim, above) I had to leave out column headings for 'security' reasons. Column 1 is the sample number (e.g. 76-9). Column 2 is Effect A (e.g. HN) and Column 3 is Effect B (e.g. Control). Effect A has 7 levels, Effect B has 4 levels. There are several response variables in the table. During the initial two-way ANOVA run, I used Column 11 (fourth from the right, e.g. 1.2 at the top). The problem seems to rest with the control level. By the way, there are 10 observations (or tested subsamples) of each replicate; for instance, there are 10 HN x Low x 4 replicates = 40. Ditto with Control.

I hope this makes sense. This is an interactive study where both treatments (A and B) were added to each exp. unit.

Thanks in advance! -LH

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

Jun 12, 2016 12:21 PM
(584 views)

Mark,

I can paste this table because it doesn't reveal what I'm studying:

By the way, 'C' is also 'Control' - I thought that it would help if I changed one of them. This is the interaction table - similar results for Effects A and B, i.e. Control interactions are 'NonEstimable'. Thanks. -LH