If I have two models:

>  m1 ~ lmer ( y1 ~ x1 + ( 1 | subject) )
>  m2 ~ lmer ( y2 ~ x1 + ( 1 | subject) )

and
m1: fixed effects t-value x1 = 25
m2: fixed effects t-value x1 = 5

is there a way to calculate whether there is a statistical difference in
the prediction of y1 vs y2 by x1, i.e. whether y1 is predicted in a
significantly stronger way by x1 that y2? Something like ... R or eta
square maybe?

Thank you
Eiko

(PS.: the solution of transforming the data and using a multivariate
response y and then calculating the interaction y~y_type*x is an option I'm
exploring currently, but I wonder what a solution would be in separate
univariate models)

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