nav[aria-label="Primary Navigation"] { padding: 0; & ul { list-style: none; width: 100%; display: flex; flex-direction: row; justify-content: start; align-items: start; gap: 30px; padding: 0; & li { margin: 0; } & ul li { list-style: none; } } }

How to test for non-additivity in a 3 factors RCBD ANOVA?

Juno

As mentioned in the title. The three factors are entry, location, and year.

Don't know how to test for non-additivity in JMP? Thank you!

Accepted answers

Mark_Bailey

Yes.

All comments

Mark_Bailey

What do you mean by 'non-additivity?'

I suspect that it means the presences of effects in the response that are not only the additive main effects. If that guess is correct, then include cross-terms to test for interactions.

Juno

I am trying to see of the 3 factors are additive in the model.

Do you mean through running a full factorial ANOVA including 2way and 3way interactions, if any of the interactions terms are significant, the additivity of the three factors are not accepted ?

Mark_Bailey

Yes.

Juno

Thank you very much!

bordini

Please, would you be able to give me the steps to test for nonadditivity in JMP and how to interpret the results? I would appreciate if you could help me. I have data from a two-factorial experiment.

PS: I'm a beginner in Statistics and in JMP.

Thank you very much,

Isadora

cwillden

If your experiment has 2 factors (say X1 and X2), just add higher-order model terms such as X1*X2, X1*X1, and X2*X2 to your model as @Mark_Bailey suggested (I'm assuming you're using Fit Model for your analysis). If the p-values for any of those effects are significant, then the relationship is not additive. Do you need help adding higher order terms to your model?

bordini

Hi,

Thank you for your reply and explanation. And yes, I need help adding higher order terms to my model, please.

Thank you very much!