The formulas for the survival probabilities are given in the Details => Survivor Function Estimators section of the PROC PHREG documentation.  These formulas are not easily replicated outside of PHREG and we rarely, if ever, get asked about them.  The only one that seems tractable is for METHOD=PL (product limit).  This estimate is S(t) = So(t)**exp(XBETA) where So(t) is the baseline survival function (more on this later) and XBETA is the linear predictor XBETA = b1*x1 + b2*x2 + . . . . + bk*xk. The bi are the coefficients and xi are the covariate values for a particular observation.     The baseline survival function So(t) can be had using the BASELINE statement and OUT= data set where the COVARIATES= data set/option has a zero value for all of the covariates.  Then you can manually put together S(t) = So(t)**exp(XBETA).     Note that the BASELINE statement is typically used in conjunction with the PLOTS= option to produce survival curves.  These curves are produced at the settings given in the COVARIATES= data set.   The COVARIATES= data set typically only has a few observations used for plotting particular survival curves.  See Example xx.8 Survival Curves in the PHREG documentation (Examples section) for an illustration.  The BASELINE statement produces estimates at the event times in the data.    Also note that if you are using the model (t1, t2) counting-process syntax then the BASELINE statement enforces METHOD=Breslow regardless of what METHOD= option you specify.  I think a NOTE is written to the log in this case.  ... View more

When using the EVENTCODE= option for a competing risks analysis PROC LIFETEST does not support the ATRISK plot option. ... View more

Tom: You can get the survival probability in this manner: use the OUTPUT statement to request the CDF= keyword and post-process this as Survival = 1 - CDF in a subsequent DATA step. I'm not sure how to get a cumulative incidence value since PROC LIFEREG doesn't model any competing risks scenario for which the CIF is appropriate. ... View more

You are correct that PROC PSMATCH does not match with more than two groups (treatment and control).  I am not aware of a procedure that does matching of 3 groups.  ... View more

Shouldn't you be specifying a FAILCODE= value in your code?   proc lifetest data=Phreg12121 plots=cif(test cl) outcif=survival_data; time T_FI1YR*outcome(0)/failcode; strata cohort ; *WEIGHT weight0_SD; run; ... View more

There is nothing similar to the "pdiff lines" options for the ADJUST= option in PROC LIFEEST. ... View more

Robust standard errors are produced by the COVSANDWICH(AGGREGATE) option on the PROC PHREG statement. You will also need an ID statement to list the variable that defines your clusters. ... View more

You may need to put your interaction terms in programming statements inside the procedure if they involve the time variable. Then you can list them in the MODEL statement as well. This would be for so-called "time-dependent interactions with time" variables. ... View more

There is no log-rank test with PROC PHREG. You can get a log-rank test in PROC LIFETEST with the STRATA statement. ... View more

I don't know if PROC PSMATCH was based on TWANG or not but it does propensity score matching of treatment and control groups. ... View more

I think you should go with the start, stop counting-process syntax.   Your data are already in that form.  ... View more

You can try using the  CONCORDANCE option on the PROC PHREG statement.  I don't know if that's enabled, necessarily, for the competing risks analysis.   ... View more

Because you don't have a COVARIATES= option/data set you are getting the default behavior in the BASELINE statement of producing only the reference level of group.  You need to define a COVARIATES= option/data set where you specify both groups.   See the example in the documentation titled "Survival Curves" for an example of using the COVARIATES= option.  I think you would also need to use the CUMHAZ= keyword on the BASELINE statement.   ... View more