generalized linear mixed model

Lately, I’ve gotten a lot of questions about learning how to run models for repeated measures data that isn’t continuous.

Mostly categorical. But once in a while discrete counts.

A typical study is in linguistics or psychology where (more…)

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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…)

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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. (more…)

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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…)

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Like some of the other terms in our list–level and  beta–GLM has two different meanings.

It’s a little different than the others, though, because it’s an abbreviation for two different terms:

General Linear Model and Generalized Linear Model.

It’s extra confusing because their names are so similar on top of having the same abbreviation.

And, oh yeah, Generalized Linear Models are an extension of General Linear Models.

And neither should be confused with Generalized Linear Mixed Models, abbreviated GLMM.

Naturally. (more…)

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Generalized linear models, linear mixed models, generalized linear mixed models, marginal models, GEE models.  You’ve probably heard of more than one of them and you’ve probably also heard that each one is an extension of our old friend, the general linear model.

This is true, and they extend our old friend in different ways, particularly in regard to the measurement level of the dependent variable and the independence of the measurements.  So while the names are similar (and confusing), the distinctions are important.

It’s important to note here that I am glossing over many, many details in order to give you a basic overview of some important distinctions.  These are complicated models, but I hope this overview gives you a starting place from which to explore more. (more…)

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