piecewiseExp_MLE: Estimate hazard function in piecewise Exponential survival...

In eventTrack: Event Prediction for Time-to-Event Endpoints

Estimate hazard function in piecewise Exponential survival model

Description

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.

Usage

piecewiseExp_MLE(time, event, K)

Arguments

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

Value

A list containing the following objects:

tau	The maximum likelihood estimates of the change points.
lambda	The maximum likelihood estimates of the value of the hazard function.
lambda.SE	The standard errors of lambda.
K	Number of change points to be used in the model.

Author(s)

Kaspar Rufibach (maintainer)
[e-mail]

References

Fang, L., Zheng, S. (2011). A hybrid approach to predicting events in clinical trials with time-to-event outcomes. Contemp. Clin. Trials, 32, 755–759.

Goodman, M.S., Li, Y., Tiwari, R.C. (2011). Detecting multiple change points in piecewise constant hazard functions. J. Appl. Stat, 38(11), 2523–2532.

Examples

# see vignette

eventTrack documentation built on April 4, 2025, 2:34 a.m.