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eventTrack (version 1.0.4)

Event Prediction for Time-to-Event Endpoints

Description

Implements the hybrid framework for event prediction described in Fang & Zheng (2011, ). 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.

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Install

install.packages('eventTrack')

Monthly Downloads

227

Version

1.0.4

License

GPL (>= 2)

Maintainer

Kaspar Rufibach

Last Published

February 22nd, 2025

Functions in eventTrack (1.0.4)

piecewiseExp_profile_loglik_tau

Profile maximum log-likelihood function for change points in piecewise Exponential survival model
exactDatesFromMonths

Compute exact timepoint when a certain number of events is reached, based on monthly number of events
hybrid_Exponential

Estimate survival function, as hybrid between Kaplan-Meier and Exponential tail
piecewiseExp_test_changepoint

Wald test to infer change point in piecewise Exponential survival model
eventTrack-package

Event Prediction for Time-to-Event Endpoints
bootstrapTimeToEvent

Bootstrap the predicted time when a given number of events is reached, for hybrid Exponential model
predictEventsUncond

compute expected number of events based on a fixed survival function and with no recruited patients yet
lambda_j_Exp

Compute lambda_j
piecewiseExp_MLE

Estimate hazard function in piecewise Exponential survival model
predictEvents

Compute timepoint when a certain number of events in a time-to-event study is reached
bootSurvivalSample

Bootstrap survival data
kaplanMeier_at_t0

Compute value of Kaplan-Meier estimate at a given time