BookmarkSubscribeRSS Feed
deleted_user
Not applicable
I am looking for a procedure (or similar) in SAS that will analyze fractional response dependent variables, i.e., variables than range continuous from 0 to 1 inclusive. Does PROC GLM handle such?
3 REPLIES 3
Doc_Duke
Rhodochrosite | Level 12
Yes and No. GLM can be used when the range of the data is limited. You will often see it used on responses that are 0-100 (like % grades) and that is analogous to your 0-1 range.

However, the assumption of normality is violated and you need to use the Central Limit Theorem to make useful inferences. In practice, this means that the closer your outcomes are to the extreme points in the distribution, the larger your sample size needs to be.

"Large" is a relative term. It would be prudent to do some bootstrap validation of your model to make sure that the parameter estimates are stable.
deleted_user
Not applicable
Are you familiar with (or is anyone familiar with) Papke and Wooldridge, 1996, and how they treat fractional response variables?
mg
Calcite | Level 5 mg
Calcite | Level 5
I'm dealing with similar problem .. have you been able to figure it out? What have you used?

sas-innovate-2024.png

Don't miss out on SAS Innovate - Register now for the FREE Livestream!

Can't make it to Vegas? No problem! Watch our general sessions LIVE or on-demand starting April 17th. Hear from SAS execs, best-selling author Adam Grant, Hot Ones host Sean Evans, top tech journalist Kara Swisher, AI expert Cassie Kozyrkov, and the mind-blowing dance crew iLuminate! Plus, get access to over 20 breakout sessions.

 

Register now!

What is Bayesian Analysis?

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.

Click image to register for webinarClick image to register for webinar

Classroom Training Available!

Select SAS Training centers are offering in-person courses. View upcoming courses for:

View all other training opportunities.

Discussion stats
  • 3 replies
  • 675 views
  • 0 likes
  • 3 in conversation