| pow.SEPPLE.plus {DelayedEffect.Design} | R Documentation |
SEPPLE+ power computation
Description
Perform the power calculation using the numeric SEPPLE+ method based on the generalized 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.
Usage
pow.SEPPLE.plus(lambda1, tl, tu, N, HR, tao, A, 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 |
dist |
One of "uniform", "beta" or "gamma", for the lag distribution |
shape1 |
NULL or a positive parameter value for the |
shape2 |
NULL or a positive parameter value for the |
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.random.DE, pow.sim.logrk.random.DE
Examples
lambda1 <- 0.001982
tl <- 30
tu <- 30*11
N <- 200
HR <- 0.55
tao <- 365*3
A <- 365
shape1 <- 5
shape2 <- 5
pow.SEPPLE.plus(lambda1, tl, tu, N, HR, tao, A, dist="beta",
shape1=shape1, shape2=shape2, nsim=1000)