I love working with my clients.
I love working with my clients for many reasons, but one of them is I learn so much from them.
Just this week, one of my clients showed me how to get SPSS GENLINMIXED results without the Model Viewer.
She’s my new hero.
If you’ve ever used GENLINMIXED, the procedure for Generalized Linear Mixed Models, you know that the results automatically appear in this new Model Viewer. (more…)
How should I build my model?
I get this question a lot, and it’s difficult to answer at first glance–it depends too much on your particular situation.
There are really three parts to the approach to building a model: the strategy, the technique to implement that strategy, and the decision criteria used within the technique. (more…)
One question I always get in my Repeated Measures Workshop is:
“Okay, now that I understand how to run a linear mixed model for my study, how do I write up the results?”
This is a great question.
There are many pieces of the linear mixed models output that are identical to those of any linear model–regression coefficients, F tests, means.
But there is also a lot that is new, like intraclass correlations and (more…)
Repeated measures ANOVA is the approach most of us learned in stats classes for repeated measures and longitudinal data. It works very well in certain designs.
But it’s limited in what it can do. Sometimes trying to fit a data set into a repeated measures ANOVA requires too much data gymnastics.
One of the things I love about MIXED in SPSS is that the syntax is very similar to GLM. So anyone who is used to the GLM syntax has just a short jump to learn writing MIXED.
Which is a good thing, because many of the concepts are a big jump.
And because the MIXED dialogue menus are seriously unintuitive, I’ve concluded you’re much better off using syntax.
I was very happy a few years ago when, with version 19, SPSS finally introduced generalized linear mixed models so SPSS users could finally run logistic regression or count models on clustered data.
But then I tried it, and the menus are even less intuitive than in MIXED.
And the syntax isn’t much better. In this case, the syntax structure is quite different than for MIXED. (more…)
The ICC, or Intraclass Correlation Coefficient, can be very useful in many statistical situations, but especially so in Linear Mixed Models.
Linear Mixed Models are used when there is some sort of clustering in the data.
Two common examples of clustered data include: