Dear SAS Communities,
I need to model a binary outcome (event = 1, nonevent = 0) depends on time. (please see the attached picture)
I would greatly appreciate guidance on which proceedures are applicable. The PROCs I tried thus far appear to model continuous outcomes.
Thank you!
Dan
What procedures have you tried? PROC LOGISTIC sounds like a place to start. Se documentation here
https://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#logistic_toc.htm
Are you looking at "time to event" type data? Such as time until failure of a part or how long the rat lives after exposure to your favorite carcinogen. Then you might want to look at survival analyis procedures such as Phreg, Lifereg, Lifetest or Probit
I am woundring how to model such data
Date | Rainfall amount (millimetres) | rain |
1/1/00 | 0.4 | 1 |
1/2/00 | 0 | 0 |
1/3/00 | 0 | 0 |
1/4/00 | 3.4 | 1 |
1/5/00 | 1.4 | 1 |
1/6/00 | 0 | 0 |
1/7/00 | 0 | 0 |
1/8/00 | 0 | 0 |
1/9/00 | 0 | 0 |
1/10/00 | 2.2 | 1 |
1/11/00 | 0 | 0 |
1/12/00 | 0 | 0 |
1/13/00 | 0 | 0 |
1/14/00 | 0 | 0 |
1/15/00 | 0 | 0 |
1/16/00 | 0.4 | 1 |
1/17/00 | 0.8 | 1 |
1/18/00 | 0 | 0 |
1/19/00 | 0 | 0 |
1/20/00 | 0 | 0 |
The rain column is the binary outcome (dependent variable).
Are you ready for the spotlight? We're accepting content ideas for SAS Innovate 2025 to be held May 6-9 in Orlando, FL. The call is open until September 25. Read more here about why you should contribute and what is in it for you!
Learn the difference between classical and Bayesian statistical approaches and see a few PROC examples to perform Bayesian analysis in this video.
Find more tutorials on the SAS Users YouTube channel.