|Date: ||Thu, 13 May 2004 13:20:17 -0500|
|Reply-To: ||"Copeland, Laurel" <Laurel.Copeland@MED.VA.GOV>|
|Sender: ||"SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>|
|From: ||"Copeland, Laurel" <Laurel.Copeland@MED.VA.GOV>|
|Subject: ||Re: Dependent variable is ratio of continuous values|
Thank you! I have put it at this location:
From: Droogendyk, Harry [mailto:firstname.lastname@example.org]
Attachments are stripped by the list serve.
From: Copeland, Laurel [mailto:Laurel.Copeland@MED.VA.GOV
Sent: Thursday, May 13, 2004 1:30 PM
Subject: Re: Dependent variable is ratio of continuous values
Some issues regarding analysis of ratios are addressed in the attached PDF
by Richard Goldstein, which I copied from a Univ Virginia Health System site
no longer in existence.
On Tue, 11 May 2004 16:35:37 -0400, Talbot Michael Katz <topkatz@MSN.COM>
>I have a situation where the target variable I want to model takes on
>values between 0 and 1, endpoints inclusive, because it is a ratio of
>two continuous quantities (e.g., actual sales / sales target)...
>Is there a "preferred" method for modeling ratios of continuous
quantities, and if so, is it available in SAS?
> Someone suggested the use of the PROC LOGISTIC events/trials syntax,
>but the SAS documentation for that really seems to stress binary
>Is it legitimate to use PROC LOGISTIC events/trials for continuous
>numerator and denominator?
>An econometrics textbook ("Econometric Analysis" by W.H. Greene, 5th
>edition, Prentice-Hall) suggests Minimum Chi-Squared Estimation (or
>don't tell Microsoft!) for proportions; it looks like that discussion
>was motivated by proportions of binary outcomes, but I think the
>equations still work in the case of continuous numerator and
>denominator. However, a
>search of support.sas.com didn't turn up any procedures that support
>the MCSE methodology. One weakness of MCSE is that the estimation only
>works when the proportion does not take on the extreme values of 0 or
>1. In such cases, it seems that the suggested work-around is to add or
>Is there a SAS procedure that does minimum chi-squared estimation for
>I could also transform the ratio from the unit interval to the entire
>line with the logit transform, log(y/(1-y)), and then perform a
>standard regression. Again, I'd have to smudge the extreme values
>before performing the transformation...
>Is it legitimate to logit transform the ratio after slightly modifying
>the extreme values, and then do OLS?
>Thanks, as ever, for your indulgence...
>-- TMK --