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
- :
- "Three-way ANOVA" on JMP?

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 17, 2014 12:41 AM
(4351 views)

Hi all,

My two questions are rather straightforward. Perhaps the question already have been posted, if so you may share a link for that discussion.

1. Is it possible to conduct a three way interaction using JMP software? i.e. a so-called 3-way ANOVA, although it doesn't go by that name I think.

2. If you can conduct "3-way ANOVAs", which function(s) of JMP are you using?

My goal is to find out the significance values of the interactions of different plant traits that are coupled under treatment (disease) x accession (or genotype) x time. Time is a variable that have two defined time points only. If using only two different interaction parameters it can be conducted using the JMP Fit Model platform for making two-way ANOVA interaction. This I have done before.

If anyone is willing to give a helping hand, I will be most happy!

Best regards,

Jim

2 ACCEPTED SOLUTIONS

Accepted Solutions

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

Sep 17, 2014 6:10 AM
(5352 views)

Solution

Hi Jim,

Using **Analyze > Fit Model** you can specify your 3-way factorial ANOVA manually or using the Macro > Full Factorial after selecting your factors in the column list. Here is a PDF showing the steps for fitting a 2-way factorial ANOVA (which generalizes to the three-way):

http://www.jmp.com/academic/pdf/learning/04_two_way_factorial_anova.pdf

The steps for a 3-way ANOVA are identical -- when you use the "Macro" for "Full Factorial" JMP will populate the *Model Effects* section with the main effects, 2-way interactions, and the 3-way interaction. Be sure that your predictor variables are all marked as Nominal.

I hope this helps!

Julian

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

Sep 17, 2014 6:18 AM
(5351 views)

Solution

Use Analyze > Fit Model, putting your response in Y box and then simultaneously highlight your three factors and select Full Factorial from Macros pull-down menu (located to the left of the Effects in Model section of the dialog box). This will fill your Effects in Model box with the three main-effects, the three two-way interactions and the three-way interaction between your factors.

3 REPLIES

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

Sep 17, 2014 6:10 AM
(5353 views)

Hi Jim,

Using **Analyze > Fit Model** you can specify your 3-way factorial ANOVA manually or using the Macro > Full Factorial after selecting your factors in the column list. Here is a PDF showing the steps for fitting a 2-way factorial ANOVA (which generalizes to the three-way):

http://www.jmp.com/academic/pdf/learning/04_two_way_factorial_anova.pdf

The steps for a 3-way ANOVA are identical -- when you use the "Macro" for "Full Factorial" JMP will populate the *Model Effects* section with the main effects, 2-way interactions, and the 3-way interaction. Be sure that your predictor variables are all marked as Nominal.

I hope this helps!

Julian

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

Sep 17, 2014 6:18 AM
(5352 views)

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

Oct 23, 2014 9:48 AM
(2841 views)

Hej!

Thanks a lot for the help! I solved the tasks some time ago.

Sorry for a late reply. I got carried away with the analyses and forgot to reply back.

Best regards,

Jim