pw_exp_impute: Imputes time-to-event outcomes.

In bayesCT: Simulation and Analysis of Adaptive Bayesian Clinical Trials

Description

Imputation of time-to-event outcomes using the piecewise constant hazard exponential function.

Usage

pw_exp_impute(time, hazard, maxtime = NULL, cutpoint = NULL)

Arguments

time	vector. The observed time for patient that have had no event or passed maxtime.
hazard	vector. The constant hazard rates for exponential failures.
maxtime	scalar. maximum time before end of study.
cutpoint	vector. The change-point vector indicating time when the hazard rates change.

Value

a dataset with simulated follow-up time (time) and respective event indicator (1 = event, 0 = censoring)

Examples

pw_exp_impute(time = c(120), c(0.005, 0.001), 110, 40)
          pw_exp_impute(time = c(10, 20, 30), c(0.005, 0.01, 0.02), 100, c(40, 80))
          pw_exp_impute(time = c(40, 30), c(0.005, 0.01), 120, c(50))

bayesCT documentation built on July 2, 2020, 2:34 a.m.