The stpm2_standsurv estimates standardized survival curves and related measures. It also allows various contrasts between the standardized functions. It is a post-estimation command and is used after fitting an stpm2 model.
The rcsgen command generates basis function for restricted cubic splines. The command is used by my stpm2 command to fit flexible parameric survival models. It has a number of advantages over Stata’s inbuilt mkspline command, which will be demonstrated in the tutorials below.
stcrprep prepares data for estimating and modelling cause-specific cumulative incidence functions using time-dependent weights. Once the data has been prepared and the weights incorporated using stset it is possible to obtain a graph of the non-parametric estimates of the cause-specific cumulative incidence function using sts graph.
stpm2 fits flexible parametric survival models. These models use splines to model some transformation of the survial function. The most common is the $\log[-\log[S(t)]]$ link function, which fits proportional hazards models.