= Solution
At an added <potential event time> with no event and a nonempty <risk set>, $d_j=0$, so <maximum likelihood estimation> gives $\widehat q_j=0$. 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 \b[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.
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