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 i
On Fri, Jul 22, 2011 at 2:04 PM, Terry Therneau wrote:
> For time scale that are truly discrete Cox proposed the "exact partial
> likelihood".
Or "the method of partial likelihood" applied to the discrete logistic model,
> I call that the "exact" method and SAS calls it the
> "discrete" method.
> From: thern...@mayo.edu
> To: abouesl...@gmail.com
> Date: Fri, 22 Jul 2011 07:04:15 -0500
> CC: r-help@r-project.org
> Subject: Re: [R] Cox model approximaions (was "comparing SAS and R
> survival)
>
>
For time scale that are truly discrete Cox proposed the "exact partial
likelihood". I call that the "exact" method and SAS calls it the
"discrete" method. What we compute is precisely the same, however they
use a clever algorithm which is faster. To make things even more
confusing, Prentice int
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