I am getting some strange output and several of my interactions are reporting 0 degrees of freedom. Would somebody mind reviewing my assumptions of nestedness and habitat? I think combining the nested variable with the repeating variable is the source of my errors. If you see an error in my code, would you mind pointing it out?
Statistician speaking up: Zero degrees of freedom always means your design does not allow you to estimate all the terms in the model. Or to put things a different way, it means that some of your interactions are completely confounded with each other, or completely confounded with main effects. Since its too late to change the design, the only thing you can do is to take some terms out of the model, and then you should wind up with all terms having positive degrees of freedom, but that does not eliminate the confounding, it only eliminates zero degrees of freedom from the model, and your effect estimates and still confounded. Sometimes the ALIASING option in PROC GLM can provide the information needed to determine what interactions are confounded with other terms in the model. In other words, the error may not be in your code, the error may be the design of the experiment.
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