topic Re: Estimate Mean Quartiles of Logistic Regression in Statistical Procedures

Estimate Mean Quartiles of Logistic Regression

nyc1989 — Mon, 05 Jul 2021 23:27:07 GMT

I've conducted a multivariable logistic regression to assess the impact of various characteristics (demographics, region, disease) on the continuous outcome- days spent in hospital. I'm interested in looking at the Q1 and Q3 quartile information of the adjusted estimate for each of the cohorts I'm looking at. What is the best way to do that?

I can't seem to find how to add that within the ls means statement

proc logistic data= data; class gender race education cancer heart_failure cohort model days= cohort gender age race cancer heart_failure education; lsmeans cohort; run;

Re: Estimate Mean Quartiles of Logistic Regression

Reeza — Mon, 05 Jul 2021 23:32:04 GMT

I think you want the ESTIMATE or ODDSRATIO statement though I'm drawing a blank on the Q1/Q3 quartile portion of that statement.

Re: Estimate Mean Quartiles of Logistic Regression

SteveDenham — Tue, 06 Jul 2021 12:54:00 GMT

I think you are going to have to export a dataset with all of the predicted values for each observation, and then post-process that dataset (probably with PROC MEANS or SUMMARY) to get the quantile estimates. I suppose my question on this approach would be: why not do that with the raw data?

The other possibility is to use an option on the LSMEANS statement, with ALPHA=0.25 and CL. That should give the 25th percentile as the lower bound and the 75th percentile as the upper bound. From there you can post-process as needed.

SteveDenham

Re: Estimate Mean Quartiles of Logistic Regression

nyc1989 — Tue, 06 Jul 2021 18:27:25 GMT

Thanks the lsmeans alpha solution worked!