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Analyze Latin squares using JMP

paul1

Occasional Contributor

Joined:

Feb 7, 2017

Hi,

I would like to analyse some data that is based on a Latin squares design. I have imported the data into JMP, two columns corresponding to the separate blocking variables, one column corresponding to the treatment variable and one column corresponding to the response. However, I am unable to specify more than I blocking column in the Fit Y by X platform. I searched through the discussion archives but could not find an answer, and would greatly appreciate any help.

 

Best,

Paul

1 ACCEPTED SOLUTION

Accepted Solutions
markbailey

Staff

Joined:

Jun 23, 2011

Solution

Jim is correct. The Oneway platform (through Fit Y by X) is intended for a one-way analysis of variance with the exception of including a single blocking variable. This requires a special role in Oneway. The more general Fit Least Squares platform (through Fit Model) is what you want.

Blocking is not a 'role' here as it is in Oneway. Instead, you simply enter the term for the treatment factors and each blocking factor, two of them in the case of your Latin square design.

The only other distinction is if you see the effect of the blocking as fixed or random. So far, JMP will model it as a fixed effect. If you want to estimate it as a random effect, then select the term in the list of effects and the click the red triangle for Attributes and select Random Effect.

Learn it once, use it forever!
3 REPLIES
txnelson

Super User

Joined:

Jun 22, 2012

You will want to use the Fit Model Platform.

Jim
paul1

Occasional Contributor

Joined:

Feb 7, 2017

I can add the response column to Y, and the treatments column to 'Construct Model Effects', but I am still not clear on how to set the other two columns as blocking. 

 

Best,

Paul

markbailey

Staff

Joined:

Jun 23, 2011

Solution

Jim is correct. The Oneway platform (through Fit Y by X) is intended for a one-way analysis of variance with the exception of including a single blocking variable. This requires a special role in Oneway. The more general Fit Least Squares platform (through Fit Model) is what you want.

Blocking is not a 'role' here as it is in Oneway. Instead, you simply enter the term for the treatment factors and each blocking factor, two of them in the case of your Latin square design.

The only other distinction is if you see the effect of the blocking as fixed or random. So far, JMP will model it as a fixed effect. If you want to estimate it as a random effect, then select the term in the list of effects and the click the red triangle for Attributes and select Random Effect.

Learn it once, use it forever!