Thank you for the helpful posts. My question was related to getting adjusted medians. I am aware of how to get quartile with confidence intervals from a post by @Rick_SAS (https://blogs.sas.com/content/iml/2017/02/22/difference-of-medians-sas.html). However, that gives me unadjusted medians as there is nothing on the right side of the model!. There is also option to predict the quantiles. Using this approach, I proceed to calculate the adjusted (predicted medians, using q=0.5). For example in the sashelp.heart study if I am interested to know the median of the diastolic blood pressure across the quartiles of the systolic pressure, this is how I got the medians adjusted for age at start and sex. *First I make quartiles of the systolic blood pressure; proc rank data=sashelp.heart groups=4 out=heart; var Systolic; ranks sys; run; *Then I get age and sex adjusted predicted diastolic blood pressure; proc quantreg data=heart ci=sparsity/iid algorithm=interior(tolerance=1.e-4); class sex; model diastolic =ageatstart sex / quantile=0.5; output out=predictquant p=predquant; run; "Then I get adjusted medians (from predicted systolic blood pressure called predquant) across the quartiles of systolic blood pressure (sys), I keep original variable to get the difference in medians; proc means data=predictquant median; class sys; var diastolic predquant ; run; I can see that the difference between median of the original variable and predicted (which is adjusted for age and sex). On a side note, to cross check my result when I added used height only for adjustment (assuming it will be less related to diastolic blood pressure), I get median of the original as well as predicted diastolic blood pressure as same. Now the question is: Is this a correct approach to get adjusted medians (The question is not about whether this is a correct data anlaysis approach!) Thanks in advance
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