With TYPE=CS on the 2nd RANDOM statement, you are likely getting a message in the log that says either the G matrix is non-positive definite or the Hessian is non-positive definite. You are also likely to see that the CS parameter in the GLIMMIX output is 0, or that if you remove TYPE=CS then you will see that two of the parameters in the model with TYPE=CS sum to one of the parameters in the model without TYPE=CS.
In the slide you reference, the second RANDOM statement with SUBJECT=PTID correlates all of the observations from the same patient. The first RANDOM statement, with SUBJECT=EYE(PTID) and leaving off TYPE=CS, correlates the observations from the same eye within a subject. If you use the V option as I suggested earlier, you will see a block diagonal covariance structure that shows this correlation pattern. Here is an example:
This is the result of the V option for 2 subjects. The first 3 rows and columns are for 3 observations on eye 1 for subject 1. Rows and columns 4-6 are for 3 observations on eye 2 for subject 1. This structure was obtained without using TYPE=CS on the RANDOM statement for SUBJECT=EYE(PTID). You get a correlation within the eyes and within all observations on the same subject.
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