 Solution

At an added potential event time with no event and a nonempty risk set, $d_j=0$, so maximum likelihood estimation gives ${\hat{q}}_j=0$. Its factor in the Kaplan–Meier estimator is therefore $1-d_j/r_j=1$.

Adding or deleting such times also leaves the risk sets at actual event times unchanged: those depend on the observed event and censoring histories. Consequently the fitted survivor function depends only on observed event times and their risk sets. Beyond the last observed follow-up, the tail is not identified; the standard flat continuation is a convention, rather than an additional consequence of likelihood maximization.