BookmarkSubscribeRSS Feed
Lapis Lazuli | Level 10

I have clustered data (right and left hand - not all patients contribute both) and I am trying to run a multinomial model in GLIMMIX. My categorical outcome is actually ordinal in nature (5 categories self rating, about 400 observations total), but I am also okay with it being treated as nominal depending on better model fit. My questions are:

1) How do I check the proportional odds assumption using GLIMMIX?

2) I am running the dist=multinomial with both the clogit and glogit links but I cannot run a model without some sort of a error or note in the log. I either get "NOTE: At least one element of the (projected) gradient is greater than 1e-3." or "NOTE: Estimated G matrix is not positive definite." singly or both together when a tweak the model using various options such as "method=laplace, nloptions MAXITER=5000 gconv=0." I was hoping someone could provide some general advice on what else I can do to fix the errors? 


Thank you. 

Obsidian | Level 7

I'm not sure about the test for the proportional odds assumption in GLIMMIX.


But the error that you are getting is because your data is sparse and is not sufficient for the model you are specifying. Possible solutions would be to reduce the number of covariates or try to make your outcome binary. You can run a simple proc freq on your outcome stratified by cluster to get a general idea on how sparse your data is.


I hope that helps!




Ready to join fellow brilliant minds for the SAS Hackathon?

Build your skills. Make connections. Enjoy creative freedom. Maybe change the world. Registration is now open through August 30th. Visit the SAS Hackathon homepage.

Register today!
What is ANOVA?

ANOVA, or Analysis Of Variance, is used to compare the averages or means of two or more populations to better understand how they differ. Watch this tutorial for more.

Find more tutorials on the SAS Users YouTube channel.

Discussion stats
  • 1 reply
  • 2 in conversation