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Level II

Interpreting Mixed Model

Hi All,


Several questions regarding linear mixed models.

1) In the "Fit Mixed" personality is there a way to get the prediction expression (Y=Bx+Zu+E), I can get it from other model personalities but can't find it in the "Fit Mixed" personality

2) I am looking at swimming performance in fish, I have two continuous fixed effects and their interaction fit against a continuous response with individual and all its interactions selected as random effects (in total 3 fixed effects:2independent and 1 interaction and 4 random effects)

          2a) when I am interpreting the random variance components is the residual in that table the variance left to be explained by the fixed effects?

          2b) If I am getting significant random variance components and significant fixed effects are my fixed effects significant BECAUSE of the random covariance            or INSPITE of the random covariance?

3) I am working with acceleration which appears to be non-linear and my model fits better when it is log transformed. Am I justified in transforming only acceleration and not my other continuous variables (which appear to be normal or nearly normal) or should I be transforming them all.


Here are a couple of screen grabs





Thanks in advance



Re: Interpreting Mixed Model

1. From the red triangle, Save columns, save prediction formula.

expression is in a new column


I don't see a residuals table in the attached report, however

Marginal Model Inference: Produces plots based on marginal predicted values and marginal residuals. These plots display the variation due to random effects.


Conditional Model Inference: Produces plots based on conditional predicted values and conditional residuals. These plots display the variation that remains, once random effects are accounted for.



3. I'm not familiar with fish acceleration. Either a log or some sort of Box-Cox transform seems like it might be reasonable.


JMP Systems Engineer, Pharm and BioPharm Sciences
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