kaplanMeier_at_t0

Compute value of Kaplan-Meier estimate at a given time \(t_0\).

htest

survival

Implements the hybrid framework for event prediction described in Fang & Zheng (2011, <doi:10.1016/j.cct.2011.05.013>). To estimate the survival function the event prediction is based on, a piecewise exponential hazard function is fit to the time-to-event data to infer the potential change points. Prior to the last identified change point, the survival function is estimated using Kaplan-Meier, and the tail after the change point is fit using piecewise exponential.

Kaspar Rufibach

eventTrack

Event Prediction for Time-to-Event Endpoints

kaplanMeier_at_t0 function

<dl> <dt>time</dt>
<dd>Event times, censored or observed.</dd> <dt>event</dt>
<dd>Censoring indicator, 1 for event, 0 for censored.</dd> <dt>t0</dt>
<dd>Vector (or single number) of time points to compute confidence interval for.</dd></dl>

Arguments

Kaspar Rufibach (maintainer) <a href="/link/kaspar.rufibach%40roche.com?package=eventTrack&version=1.0.4" data-mini-rdoc="eventTrack::kaspar.rufibach@roche.com">kaspar.rufibach@roche.com</a>

Author

Compute value of Kaplan-Meier estimate at a given time — kaplanMeier_at_t0

<dl>

 <dt>time</dt>
<dd>Event times, censored or observed.</dd>

 <dt>event</dt>
<dd>Censoring indicator, 1 for event, 0 for censored.</dd>

 <dt>t0</dt>
<dd>Vector (or single number) of time points to compute confidence interval for.</dd>

</dl>

Kaspar Rufibach (maintainer) <a href='mailto:kaspar.rufibach@roche.com'>kaspar.rufibach@roche.com</a>

kaplanMeier_at_t0: Compute value of Kaplan-Meier estimate at a given time

Description

Usage

Value

Arguments

Author

Examples