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Thank you for your answer.  You get the point: all is about the assumption regarding the causal role or U on E and Y. I explicitly want to simulate a U that causes E and Y (as given in the dataset) but independantly of the observed covariates X ; and not a collider. If U is a collider, then my current estimation that ignores U is correct ; but if U is a confounder, it is not.  In the simulation I cannot impose a direction (a causality) but only a correlation structure between U, E and Y (and X). If there is causality (U-->E and U--Y) then I would observe the correlation structure that I simulate. More precisely I intend to simulate all that is needed to get my current estimation right without X but false if U is a confounder and to estimate the amount of correlation (causal role) of U on E and Y that would produce a null causal effect of E on Y when U is taken into account.   To be honest, I studied causal diagrams and Pearl's theory quite in detail but what I want to do is not in the textbooks I know. But I think it is relevant.    Best,  ... View more

I am sorry. I have no clue.   This paper is partially devoted to usage of the DIVISOR= option after forward slash ( / ) on ESTIMATE statement. I have read it diagonally, but could not find the answer to your question. SAS Global Forum 2010 Paper 269-2010 Practicalities of Using ESTIMATE and CONTRAST Statements David J. Pasta, ICON Clinical Research, San Francisco, CA https://support.sas.com/resources/papers/proceedings10/269-2010.pdf   As I have moved your post to the most appropriate board for it , I am confident someone will come up with the right answer.   Thanks, Koen ... View more

Hello,  DId you finally solve this problem?  I have a similar problem of interaction between a categorical and a continuous variable using proc surveylogistic and i could not figure it out.Let me know how you solved it. ... View more