Linear mixed model without random or repeated effects? GLMZ?


I'm working on a dissertation, of which many chapters have longitudinal data and I've been using linear mixed models to estimate growth. I also have some non-longitudinal data (i.e. cross-sectional) that I'd like to estimate growth with in a similar way. The cross-sectional data spans a good age-range, and I'd like to construct a model for the DV over this age period.

Can I conduct a linear 'mixed' model without random or repeated effects (is this a marginal model) to just get ML parameter estimates and build a model? Is this the same thing as a Generalized Linear Model? I get almost exactly the same parameters with each.

I'd ideally like to work within the LMM framework as I now know it pretty well, but more important is that my stats are sound!

Any help would be MUCH appreciated!


Ninja say what!?!
If you don't have repeated measures data, then it'd be best to just set up a GLM model. It's very similar to setting up GLMM, except less complicated. I haven't tried it out yet, but I imagine that setting up a mixed model without repeated measures would give you the exact same result as the linear model.