I believe the issue is that the PROC CAUSALMED code does not specify that the outcome, mediator, and treatment are binary, so as a result the CAUSALMED procedure is modeling the outcome and mediator with a normal distribution not logistic regression. You can check if this is the case by looking at the "Model Information" table produced with the example code.    Specifying the mediator and treatment variables in the CLASS statement will indicate that they are binary and you can use the DIST=bin option in the MODEL statement to indicate the outcome is binary and should be modeled using logistic regression. The third example in the documentation for PROC CAUSALMED has an example of causal mediation analysis with treatment, outcome, and mediator, all binary.   https://go.documentation.sas.com/?docsetId=statug&docsetVersion=15.1&docsetTarget=statug_causalmed_examples03.htm&locale=en     ... View more

SAS does report standard error with it.   Uno's Concordance Statistic Source Estimate Standard Error Model 0.5464 0.1584   For 95% CI: you would multiple SE with 1.96.    In the given example, it would be 0.1584*1.96 = 0.3105   Lower limit = 0.5464 - 0.3105 = 0.2359  Upper limit = 0.5464 + 0.3105 = 0.8569   Thus if rounded 0.55 (0.24, 0.86) or expressed as % then 54.6 (23.6, 85.7).   Hope this helps.   Ashutosh   ... View more

Here are some papers   1. Using SASÒ to Match Cases for Case Control Studies by Kawabata et al.   2. Using SAS® Software to Perform a Case-Control Match on Propensity Score in an Observational Study by Parsons.   3. SAS® Programs to Select Controls for Matched Case-Control Studies by Matthews and Brill   4. Matching Data Using SAS! Programming and Human Judgment by Go.   5. Simplified Matched Case-Control Sampling using PROC SURVEYSELECT by Disekar   6. Incidence-Density Sampling: Alternative Programming Approaches to Achieve the Same End by Gately and Tumbull   7. Automating the Selection of Controls in Case-Control Studies by Mounib   8. An Introduction to Matching and its Application using SAS® by Mandrekar ... View more

For correlated data, you would use ID statement. See:  https://support.sas.com/documentation/cdl/en/statug/63962/HTML/default/viewer.htm#statug_phreg_sect056.htm   When the proportional hazards assumption is not met, you would use STRATA statement. See: https://support.sas.com/documentation/cdl/en/statug/63033/HTML/default/viewer.htm#statug_phreg_sect019.htm and https://www.cibmtr.org/meetings/materials/crpdmc/documents/2010/feb2010/loganb_coxproportion1.pdf (page 7)       ... View more

Try using PROC SGPLOT on the output data. ... View more

Refer to this paper: "Mediation Analysis Allowing for Exposure–Mediator Interactions and Causal Interpretation: Theoretical Assumptions and Implementation With SAS and SPSS Macros" by Valeri and VanderWeele. ... View more

Thanks much.   Ashutosh ... View more