pow.logRank: Simulated log-rank power computation

In DelayedEffect.Design: Sample Size and Power Calculations using the APPLE, SEPPLE, APPLE+ and SEPPLE+ Methods

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) 

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.

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.

Value

The power

Author(s)

Zhenzhen Xu <[e-mail]>, Boguang Zhen<[e-mail]>, Yongsoek Park <[e-mail]> and Bin Zhu <[e-mail]>

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.

See Also

pow.APPLE, pow.SEPPLE

Examples

  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)

DelayedEffect.Design documentation built on Aug. 21, 2023, 5:07 p.m.