2.5. Fixed Effects versus Random Effects
It should come as no surprise to learn that fixed effects methods are not the only way to estimate regression models for longitudinal data. There are several popular alternatives, many of which are readily available in SAS. To fully appreciate both the strengths and weaknesses of the fixed effects method, we need to compare it with some of these alternatives.
The closest cousin to the fixed effects model is the random effects or mixed model. We start with the same basic equation:
Now, however, instead of assuming that αi represents a set of fixed parameters, we suppose that each αi is a random variable ...
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