BookmarkSubscribeRSS Feed
knallen
Calcite | Level 5

Hi all,

 

I am struggling to understand when, using proc phreg to produce a frailty model, one would use the "unadjusted" p-value vs. the adjusted. See, e.g., https://documentation.sas.com/doc/en/statcdc/14.2/statug/statug_phreg_examples11.htm 

Output 86.11.6. In this example, the adjusted p-values are cited in the text. However, I compared proc phreg frailty model results those produced from the survival package in R, and the results were closer to those from the "unadjusted" p-value. I understand that the adjusted p-value is just the Wald test with df adjusted using the Wald Adjustment, and I've studied Therneau and Grambsch (2000) and the formula for the Wald Adjustment, but from a practical point of view,  I can't figure out why the Wald Adjustment is necessary, particularly since the R output is more similar to the unadjusted case. 

Can someone explain the practical value to using the adjusted p-value? For those with experience fitting a frailty model, which result have you used when you do have a large frailty REML estimate? 

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
  • 0 replies
  • 299 views
  • 0 likes
  • 1 in conversation