Hello. I need to use PROC CAUSALMED as a part of my analysis.    My question is: how do you appropriately fit continuous variables (exposure and mediator(s) in the PROC CAUSALMED procedure? Is it important to model them as we would traditionally when setting up say a PROC GENMOD with linear regression. Or, should I 'just' insert the variables in the model 'as is' assuming the program will decide on the correct model?  Essentially:  I have >1,000 continuous mediators I would like to evaluate.  A binary outcome (0,1) with time to event   Categorical covariates on race/gender which I made into binary variables (0,1) and age which I am hoping to model as quadratic (age age_sq).  The exposure is continuous and it seemed the best way to model that was log-normalized cubic with restricted splines ( D_Dimer_ln_centered ddimers015 ddimers023 ddimers033).  I want to include interactions between my exposure and mediator.  Here is my program below that I am struggling to fit:  PROC CAUSALMED DATA=G (WHERE=(C7_INCHF20 NE .));       CLASS r_asian r_white r_black r_natamer cur_smoke for_smoke nev_smoke g_fem g_male / DESCENDING;       MODEL time_to_event*CHF= D_Dimer_ln_centered ddimers015 ddimers023 ddimers033 mediator1 /COXPH;       MEDIATOR mediator1 = D_Dimer_ln_centered; *You cannot specify more than one MEDIATOR statement in an analysis.;       COVAR r_asian r_white r_black r_natamer cur_smoke for_smoke nev_smoke g_fem g_male age age_sq; RUN;   I have reviewed the documentation for the program, but it does not mention what to do with continuous variables (other than you can) and how many variables or how to specify them in the model.  Thank you in advance for your help.  ... View more