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
![Stephen2020_0-1592308261731.png Stephen2020_0-1592308261731.png](https://community.jmp.com/t5/image/serverpage/image-id/24615iE842AA10D0DE260A/image-size/medium?v=v2&px=400)
![Stephen2020_1-1592308312397.png Stephen2020_1-1592308312397.png](https://community.jmp.com/t5/image/serverpage/image-id/24616i5CEAC9156C4880FA/image-size/medium?v=v2&px=400)
![Stephen2020_2-1592308383498.png Stephen2020_2-1592308383498.png](https://community.jmp.com/t5/image/serverpage/image-id/24617i00E62FD55F29F9C9/image-size/medium?v=v2&px=400)
![Stephen2020_3-1592308404348.png Stephen2020_3-1592308404348.png](https://community.jmp.com/t5/image/serverpage/image-id/24618iC5BC0A15574123F0/image-size/medium?v=v2&px=400)
Thanks in advance