boot_logistic {EquiSurv} | R Documentation |
Parametric Bootstrap of time-to-event data following a logistic distribution
Description
Function generating bootstrap data according to a logistic distribution (specified by a model parameter \theta
),
assuming exponentially distributed right-censoring (specified by a rate C). After data generation again a model is fitted and evaluated
at a pre-specified time point t_0
yielding the response vector.
Usage
boot_logistic(t0, B = 1000, theta, C, N)
Arguments
t0 |
time point of interest |
B |
number of bootstrap repetitions. The default is B=1000 |
theta |
parameter of the logistic distribution, theta=(location,scale) |
C |
rate of the exponential distribution specifiying the censoring |
N |
size of the dataset = number of observations |
Value
A vector of length B containing the estimated survival at t0
Examples
t0<-2
N<-30
C<-1
boot_logistic(t0=t0,theta=c(1,0.4),C=C,N=N)
[Package EquiSurv version 0.1.0 Index]