piecewiseExp_MLE

This function estimates the values of the hazard function and the change points in a piecewise Exponential survival model. The number of change points \(K\) needs to be pre-specified.

htest

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

piecewiseExp_MLE function

<dl> <dt>time</dt>
<dd>Event times, censored or observed, in months.</dd> <dt>event</dt>
<dd>Censoring indicator, 1 for event, 0 for censored.</dd> <dt>K</dt>
<dd>Number of change points to be used in the model.</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

Estimate hazard function in piecewise Exponential survival model — piecewiseExp_MLE

<dl>

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

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

 <dt>K</dt>
<dd>Number of change points to be used in the model.</dd>

</dl>

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

piecewiseExp_MLE: Estimate hazard function in piecewise Exponential survival model

Description

Usage

Value

Arguments

Author

References

Examples