The only way to get a log-rank test at 12 months and 24 months would be to subset your data to those time intervals.  That is not really something we would recommend.   I don't see any other way to get a log-rank test at a specific time instead of over all the data.  ... View more

PHREG does not produce hazard estimates.  The underlying model is h(t) = ho(t) * exp(xbeta) where ho(t) is an unknown and unspecified baseline hazard.   Cox's method of partial likelihood does away with ho(t) but still estimates the coefficients.  These coefficients are exponentiated to give hazard ratios which is the main output of PHREG.  It you have time-dependent covariates (td-covars) defined by programming statements inside the PHREG step then, as you noticed, the OUTPUT and BASELINE statements are not available.   If you could use the model (t1, t2) counting-process style of input (cp-syntax) then the BASELINE statement could be used with the CUMHAZ= keyword to get cumulative (integrated) hazard estimates.  ... View more

unfortunately, PROC SURVEYPHREG does not have the EVENTCODE= option (like PROC PHREG does) to enable a competing risks analysis.  You could try using PHREG with a WEIGHT statement; the parameter estimates would be the same but not the standard errors as from SURVEYPHREG.  ... View more

If you want curves for treated (events?) and untreated (censored?) separately then it seems you would have to run two PROC LIFETEST steps for each imputed data set.   That would mean 10 PROC LIFETEST steps. I don't see any other way around this.  ... View more

Have you tried "strata _imputation_" ?   ... View more

 I don't see anything that your are doing wrong necessarily.  Your code looks OK to me.  The BASELINE statement should be estimating the CIF at the covariate values and time you specified. We don't have a benchmark for the number of events but, as always, the more the better.  ... View more

I don't think you want a WHERE statement which would mean you would have to run PHREG 3 times to get 3 sets of estimates. Whereas a BY statement can handle this with one run of PHREG. ... View more

I think IPW weights are common but you should be able to use any WEIGHT value you desire. Note that the WEIGHT stmt only applies to Method=KM. ... View more

I noticed you have huge standard errors which are indicative of a montone likelihood problem.  We have a SAS Note on this:   Problem Note 13679: A binary or categorical covariate with no events in one level may cause monotone likelihood convergence problems resulting in large standard errors http://support.sas.com/techsup/notes/v8/13/679.html ... View more

I don't see an EVENTCODE option on the MODEL statement in PROC SURVEYPHREG. ... View more