Thanks to those who answered my question as to why SAS would set my B's = 0 for 'redundant' qualitative X's. I should have known this.
Now my questions is, how do I determine statistical significance of the parameters with B set to 0 since no p-value is given. Are DEV_WILL and GEN_CORNELL
Does the significance of the intercept term imply anything about this?
Note: The following parameters have been set to 0, since the variables are a linear combination of other variables as shown.
DEV_WILL0 = Intercept - DEV_SMITH0 - DEV_JONES0
GEN_CORNELL0 = Intercept - GEN_JACKSON0 - GEN_DAVIS0
This issue gets into parameterization, which is hard to explain via computer. But it helps to ask yourself what question you're trying to answer, which sounds basic, I know, but it's amazing how often that very clearly and very specifically defining the question helps you find the answer.
You ask how you know if CORNELL is significant. Signficant compared to what? Remember, CORNELL isn't a continuous variable such as AGE, where you get a parameter estimate and a p-value and that tells you what happens as AGE changes. Instead, CORNELL is one general.
The beta and p-value for JACKSON will tell you whether JACKSON is different from CORNELL (or equivalently whether CORNELL is different from JACKSON).
The beta and p-value for DAVIS will tell you whether DAVIS is different from CORNELL (or equivalently whether CORNELL is different from DAVIS).
And you could write a CONTRAST statement to determine whether JACKSON is different from DAVIS.
Those are typically the only kinds of questions I ask in situations like that. But there is a way to answer the question "Is CORNELL different from all generals combined?" and I don't know what it is right now but perhaps that's not what you really need to know anyway.