pow.sim.logrk: Simulated log-rank power computation

Description

Perform the power calculation using a simulation-based method based on the regular log-rank test when the treatment time-lag effect is present and the lag duration is homogeneous across the individual subject

Usage

pow.sim.logrk(lambda1, t1, p, N, HR, tao, A, ap=0.5, alpha=0.05, nsim=10000)

Value

The power

Arguments

lambda1: Baseline hazard or NULL (see details)
t1: Delayed duration or NULL (see details)
p: Proportion of subjects who survive beyond the delayed period or NULL (see details)
N: Sample size
HR: Post-delay hazard ratio, defined as the post-delay hazard rate of the treatment group compared to that of the control group
tao: Total study duration
A: Total enrollment duration
ap: Experimental-control allocation ratio. The default is 0.5.
alpha: Type I error rate (two-sided). The default is 0.05.
nsim: Number of simulations. The default is 10000.

Author

Zhenzhen Xu <Zhenzhen.Xu@fda.hhs.gov>, Boguang Zhen<Boguang.Zhen@fda.hhs.gov>, Yongsoek Park <yongpark@pitt.edu> and Bin Zhu <bin.zhu@nih.gov>

Details

Out of the three input parameters lambda1, t1 and p, only two need to be specified, the remaining one will be computed internally from the formula lambda1 = -log(p)/t1. If all three are not NULL, then lambda1 will be set to -log(p)/t1 regardless of the user input value.

References

Xu, Z., Zhen, B., Park, Y., & Zhu, B. (2017). Designing therapeutic cancer vaccine trials with delayed treatment effect. Statistics in medicine, 36(4), 592-605.

Examples

Run this code

  lambda1 <- NULL
  t1      <- 183
  p       <- 0.7
  N       <- 200
  HR      <- 0.55
  tao     <- 365*3
  A       <- 365
  pow.sim.logrk(lambda1, t1, p, N, HR, tao, A, nsim=1000)

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