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Level I

ANOVA with repeated measures. Can I have your opinion?

​Dear all,

I'm PhD Student in Agronomy and my topic is Soil Respiration. I'm currentely trying to analyse some data i've collectd from different crop fields and I've found that many authors use repeated measure ANOVA for test differences in SR among different enviroments.

So, simply put, I have different levels of soil respiration in different fields in different dates. This should work as a semplified example:

 Date Field Replicate Soil resp 1-gen-1900 A 1 0,24 1-gen-1900 A 2 0,35 1-gen-1900 A 3 0,15 1-gen-1900 B 1 0,55 1-gen-1900 B 2 0,74 1-gen-1900 B 3 0,22 5-gen-1900 A 1 0,15 5-gen-1900 A 2 0,57 5-gen-1900 A 3 0,27 5-gen-1900 B 1 0,76 5-gen-1900 B 2 0,49 5-gen-1900 B 3 0,38 15-gen-1900 A 1 0,08 16-gen-1900 A 2 0,80 17-gen-1900 A 3 0,88 18-gen-1900 B 1 0,15 19-gen-1900 B 2 0,60 20-gen-1900 B 3 0,88

Which is the procedure to perfom a repeated measure ANOVA in JMP SAS?

4 REPLIES 4
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Staff

Re: ANOVA with repeated measures. Can I have your opinion?

You can use the Mixed Models in JMP Pro's Fit Model platform for the analysis of repeated measures. See the on-line documentation for step-by-step details: Additional Examples. ​ The data used in the example, Cholesterol Stacked.jmp, can be found in the JMP Sample Data Directory (go to Help=>Sample Data Library. )

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Level I

Re: ANOVA with repeated measures. Can I have your opinion?

Thank you but I'm afraid I don't have a JMP Pro. And as I can see, I don't have the possibily to select "Mixed Model" on "personality" when I open "Fit model"

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Super User

Re: ANOVA with repeated measures. Can I have your opinion?

The "Animals" sample data table has a repeated measures example, that I believe does not require JMP Pro.

Jim
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Staff

Re: ANOVA with repeated measures. Can I have your opinion?

You can use the random effect from Attributes tab in Fit Model to perform the analysis as shown in the Animal example that Jim mentioned. Split Plot Design Example. Just keep in mind that it assumes an Compound Symmetry covariance structure, which may be considered too restrictive. JMP Po's Mixed Model offers more selections.