|Date: ||Fri, 8 Jul 2005 13:36:46 -0700|
|Sender: ||"SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>|
|Subject: ||Re: Proportion in Logistic regression|
|Content-Type: ||text/plain; charset="iso-8859-1"|
I am not sure how you group the data. I hope the following information
In Greene's Book 19.4.6 (page 835, 4th edition) Analysis of Proportions
Data. He gives an approach to deal with the groupd data.
Note: The estimated coefs maybe much smaller from grouped data than
those from individual(ungrouped) data because the variations reduce due
Manon Girard wrote:
> Hello members,
> I am stuck in a basic problem.
> My response variable is a proportion (A/B) and I have to modelized it in a
> logistic regression, then I have to estimate the treatment effects using
> predicted percents from the model.
> It my proc below would do it ?
> proc logistic data=xxx;
> class trt_grp covariates;
> model A/B=trt_grp covariates;
> output out=x predicted=p;
> When I tested it with my knowledge of logistic regression, I assumed that
> with the intercept only, this should come as the same proportion of the
> actual proportion.
> As an example, if I use a 0/1 response variable (say C), a proc like "model
> C=;", would give an estimated proportion as being the same as the proportion
> of 0/1 in my dataset.
> I followed this strategy but this doesn't seem to work this way.
> If I put the question in another way, I calculated "result=A/B" for each
> individual in my dataset. I want to see if there is a treatment effect in
> "result", while taking into account all the possible covariate. Is Logistic
> the best way to do such analysis ?