PROC GLM has many advantages over proc reg such as a case statement. But SAS has chosen not to include many of the diagnostics in proc glm that are in proc reg. The logical solution is to run the model in Proc Glm, than run the same model with diagnostics in proc reg.

The problem with this is, potentially, that you are treating dummy variables differently in the two, through the CLASS statement. Will this influence the diagnostics, that test for things like unequal error variance, non-linearity, multicolinearity etc?

I am concerned I will run the diagnostics in PROC REG and they will be ok, but not be ok in PROC GLM (really they won't be substantively correct at all) because of issues such as how dummy variables are treated differently in the two procs.

While I am at it, the RAMSEY RESET test is offered as a test for non-linearity. It is done as far as I know only in PROC AUTOREG and my data is not time series. Does anyone know if this can be used in another form of regression? I have found no examples of this on line.

The problem with this is, potentially, that you are treating dummy variables differently in the two, through the CLASS statement. Will this influence the diagnostics, that test for things like unequal error variance, non-linearity, multicolinearity etc?

I am concerned I will run the diagnostics in PROC REG and they will be ok, but not be ok in PROC GLM (really they won't be substantively correct at all) because of issues such as how dummy variables are treated differently in the two procs.

While I am at it, the RAMSEY RESET test is offered as a test for non-linearity. It is done as far as I know only in PROC AUTOREG and my data is not time series. Does anyone know if this can be used in another form of regression? I have found no examples of this on line.

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