[R] Cox model approximaions (was "comparing SAS and R survival....)

[AO_Statistics]

I have a question about Cox's partial likelihood approximations in "coxph"
function of "survival package (and in SAS as well) in the presence of tied
events generated by grouping continuous event times into intervals.
I am processing estimations for recurrent events with time-dependent
covariates in the Andersen and Gill approach of Cox's model.

If I have understood Breslow's and Efron's approximations correctly, they
consist in modifying the denominators of the contributing likelihood term
when we do not know the order of occurrence of the events. This order is
important only if the tied events are associated to a diferent value of the
covariate.
I would like to know if the "breslow" and "efron" options still modify the
initial denominators of the terms when they correspond to the same
covariate.
Especially, whithin the same trajectory of the observed process (the same
individual), the covariate is measured once for each tied events.
To my mind, we would introduce a useless bias in this case since the initial
partial likelihood is true.

Thank you.

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