pow.SEPPLE.random.DE {DelayedEffect.Design}R Documentation

SEPPLE+ power computation

Description

Perform the power calculation using the numeric SEPPLE method based on the piecewise weighted log-rank test when the treatment time-lag effect is present and the lag duration varies heterogeneously from individual to individual or from study to study, within a certain domain and following a specific pattern. The purpose of this function is to evaluate the property of SEPPLE which assumes the lag duration is homogeneous across the individual subject, when applied under the random scenario where the lag duration, in fact, varies heterogeneously.

Usage

pow.SEPPLE.random.DE(lambda1, tl, tu, N, HR, tao, A, t.fixed, dist="uniform",
              shape1=NULL, shape2=NULL, ap=0.5, alpha=0.05, nsim=10000) 

Arguments

lambda1

Baseline hazard

tl

Lower bound of delayed duration domain

tu

Upper bound of delayed duration domain

N

Sample size

HR

Post-delay hazard ratio after tu, 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

t.fixed

Fixed duration in SEPPLE

dist

One of "uniform", "beta" or "gamma", for the lag distribution

shape1

NULL or a positive parameter value for the beta or gamma distribution.

shape2

NULL or a positive parameter value for the beta or gamma distribution.

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

SEPPLE+ is an acronym for:
Simulation-based Empirical Power calculation method based on generalized Piecewise weighted Log-rank tEst with random treatment time-lag effect. See the reference for details of this method.

Value

The power

Author(s)

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>

References

Xu, Z., Park, Y., Zhen, B. & Zhu, B. (2017). Achieving optimal power of logrank test with random treatment time-lag effect. Biometrika. Under review.

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.SEPPLE.plus, pow.sim.logrk.random.DE

Examples

  lambda1 <- 0.001982
  tl      <- 30
  tu      <- 30*11
  N       <- 200
  HR      <- 0.55
  tao     <- 365*3
  A       <- 365
  t.fixed <- (tl+tu)/2
  shape1  <- 5
  shape2  <- 5
  pow.SEPPLE.random.DE(lambda1, tl, tu, N, HR, tao, A, t.fixed, dist="beta", 
                       shape1=shape1, shape2=shape2, nsim=1000)

[Package DelayedEffect.Design version 1.1.3 Index]