Covariance Estimates when Fitting Generalized Linear Mixed Model

[binfang]

I noticed there are something wrong with covariance estimates when fitting Generalized Linear Mixed Model, as it is shown below:

The model is a multinomial generalized mixed model, where the outcome is a 4-level categorical variable and all the predictors are continuous.

The SAS codes are as attached.

Can you suggest any way to fix the problem?

Thank you!

[PaigeMiller]

What is wrong with the results?

[binfang]

One estimate is 0, the other one is extremely small. And their standard error are both missing.

[PaigeMiller]

What makes a zero wrong? Those could be (and probably are) the correct calculations. 

[binfang]

Hi Paige,

The model I am trying to fit is a categorical mixed model, where the outcome is a 4-level categorical variable. This means there should only be 3 rows of estimate in the covariance output, but there are 4 rows instead, which is not what I expected since one level should be used as reference. 

I have attached the modified syntax if you are interested to run. The data is attached in the next post.

Best,

Bin

[PaigeMiller]

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@binfang wrote:

This means there should only be 3 rows of estimate in the covariance output, but there are 4 rows instead, which is not what I expected since one level should be used as reference. 

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I don't think this is correct, I think there are covariance estimates for every level of your 4-level categorical variable. But honestly, it has been a very long time since I did PROC GLIMMIX with DIST=MULTINOMIAL. Maybe someone knows.