Linear Mixed Models in SPSS: why the extra repeated measures option??

Hi all,

I've got a basic question about the interface of SPSS linear mixed models.
The initial window provides the option to designate one or more variables as "repeated measures" and to choose a separate covariance structure for these.

I noticed that not using this option doesn't do an awful lot to the parameter estimates, but there is a slight difference (seems to slightly increase the p values, although hardly noticeable).

Just wondering: why is this option given?
Isn't it enough to put the repeated measure variables in the random effects field?

Appreciate any thoughts on this!


Ambassador to the humans
I've never used SPSS but there is a difference between the two options. For instance if you just take care of repeated measures by incorporating a random effect this forces a compound symmetry structure on the covariance matrix between observations that share the same random effect. However, sometimes it might be more appropriate to use a difference covariance matrix - an AR(1) correlation structure for instance might be more appropriate for measures that are repeated over time.