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binfang
Fluorite | Level 6

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

image.png

 

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!
5 REPLIES 5
PaigeMiller
Diamond | Level 26

What is wrong with the results?

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Paige Miller
binfang
Fluorite | Level 6

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

PaigeMiller
Diamond | Level 26

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

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Paige Miller
binfang
Fluorite | Level 6

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
Diamond | Level 26

@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. 

 


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.

--
Paige Miller

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