Dear Mixed Models Mailing List.

Do I understand correctly that, for longitudinal data, the following syntax
is really not something you want to do:

Y ~ time + x1 + x2 +x3 + ( time | subject )

because significant effects on the covariates would simply refer to the
intercept of the first measurement point?

Instead, the model would have to look like this:

Y ~time (x1 + x2 +x3 ) + ( time | subject)

to have the covariates also predict differences in slope. Is that correct?

If this is the case, I don't quite understand most of the R tutorials for
mixed models out there, because they nearly all use the first notation.

Thanks for clarifying, I'm a but confused.

~~Eiko

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