Mixed Up Mixed Models

A great article for specifying Mixed Models in SAS:

Mixed up Mixed Models
by Robert Harner & P.M. Simpson

Anyone doing mixed modeling in SAS should read this paper, originally presented at SUGI: SAS Users Group International conference. It compares the output from Proc Mixed and Proc GLM when specified different ways. There are some subtle distinctions in the meaning of the defaults in the Repeated and Random statements, and this paper does an excellent job of clarifying them.


Random Intercept and Random Slope Models
Get started with the two building blocks of mixed models and see how understanding them makes these tough models much clearer.

Reader Interactions


  1. Matt says

    I’ve read through your blog and posts about random effects models and found it very useful. One thing which I can’t see a reference too, and which must be a common issue, is what to do when our main interest is in treatment differences (fixed factor) and the variances are not the same. I have a set of data with 3 treatments and one has a smaller variance. You wouldn’t pick it from the boxplot but the f test is significant as the sample size is quite large. I’ve searched the web and looked at examples and can’t find anything. This surprises me as surely this must be a common problem.
    Advise appreciated.

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