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
- :
- LSMeans Tests between Student's t vs. Tukey HSD

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

Highlighted

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

Dec 6, 2018 12:42 PM
(3228 views)

Has anyone seen this result where Student's t letters are the same while Tukey HSD letters are different. I usually see visa versa. Any thought?

1 ACCEPTED SOLUTION

Accepted Solutions

Highlighted

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

I would not perform any *post hoc* tests until I validated the assumptions of the model and addressed all the issues with the estimation.

- Did you notice the warnings in the report of the variance components?
- Did you notice that your model is over-specified and the fixed and random effects are confounded?
- Did you notice that one of the random effects is zeroed?
- How do you justify treating gender as a random effect?

I don't think that this analysis is quite ready for any *post hoc* tests.

Learn it once, use it forever!

1 REPLY 1

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

I would not perform any *post hoc* tests until I validated the assumptions of the model and addressed all the issues with the estimation.

- Did you notice the warnings in the report of the variance components?
- Did you notice that your model is over-specified and the fixed and random effects are confounded?
- Did you notice that one of the random effects is zeroed?
- How do you justify treating gender as a random effect?

I don't think that this analysis is quite ready for any *post hoc* tests.

Learn it once, use it forever!