@Dylan1 wrote: I was of the view that given the proportional hazard assumption has failed when I used the Cox. The Royston parmar was the closest option which doesnt have a number of assumptions as compared to the other models. The proportional hazards assumption is also needed in the the Royston-Parmar model, according to this source:   ... View more

Thanks for sharing. One thing I would like to further comment on is the functional form of the time-dependent variables. As has been shown in the preceding SAS code, the time-dependent variable is assumed to be linear. However, it should be noted that in theory, nonlinear versions of time-dependent variables are also permitted in Cox models. See, for instance Using fractional polynomials and restricted cubic splines to model non‐proportional hazards or time‐varying covariate effects in the Cox regression model - Austin - 2022 - Statistics in Medicine - Wiley Online Library for more on the theoretical intricacies and SAS codes of nonlinear time-dependent variables. Still, the linear time-dependent variable is the most widely used functional form in practice. ... View more

Train and test data is relevant for prediction. Then it is probably not a Cox model you want to fit, as the Cox model does not predict anything. It only estimate the hazard rate ratios. ... View more

It would be helpful to see your actual code, especially if you have used the TIMELIST= option. By default, PHREG will give you the survival probabilities for each of the unique event times and not just the number of unique times in your data.  How many unique event times do you have? ... View more

Take a look at 33307 - Scoring (computing predicted values) for new observations or a validation data set. Special thanks are given to @StatDave for introducing me this note. ... View more