The name is absent

50

∕3<^m+i) and _lβc^m+1∖ following values are not updated within Step 4:
⅛^m>(.),⅛<"^,(.)₁D<"∙>(.)and⅛^wH.

Step 5,

Let τn = m + 1, repeat Steps 2, 3 and 4 until ∕j(^m+1) and ∕3c^m+1'* converge, respec-
tively.

Furthermore, we could get estimated cumulative hazard functions Â(-) and Ψ(∙),
survival functions S(∙) and R(β) and their confidence intervals by combining results
of simulations and bootstrapping. Details are listed in Section 3.4.

3.3.5 Remarks

Another approach of the iteration

There is another approach to complete the iteration. Instead of using a separate
Step 4, we can combine Steps 2, 3 and 4 together to get the converged β and β_c. That
is to say, always update P∕^m∖∙), Q_i∙^m∖-), Lζ∙^m∖∙) and E[^m∖-^) after getting β(^m+1') and
3c^m^^l^i). We tested those two approaches of iterations. Both the results and the length
of time used are quite similar. Thus, we randomly picked the first approach to conduct
this research.

Assumption

An implicit assumption used in our method is that, the association between events
and dependent censoring is the same among different subgroups defined by covariate
values. It is plausible in most situations. This assumption would fail if, for instance,

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