| DelayedEffect.Design {DelayedEffect.Design} | R Documentation |
An R package for sample size and power calculation when the treatment time-lag effect is present and the lag duration is homogeneous across the individual subject using the APPLE and SEPPLE methods based on the piecewise weighted log-rank test. For comparison, this package also performs the power calculation based on the regular log-rank test which ignores the existence of lag effect.
The two new methods in this package for performing the sample size and power calculations are:
1. Analytic Power calculation method based on Piecewise weighted Log-rank tEst (APPLE),
2. Simulation-based Empirical Power calculation method based on Piecewise weighted Log-rank
tEst (SEPPLE).
See the reference for details of these methods and the piecewise weighted log-rank test.
The functions for computing power corresponding to the above methods are pow.APPLE and
pow.SEPPLE. These can be compared to pow.sim.logrk,
which computes the power from a simulation-based algorithm using
the regular log-rank test which ignores the existence of lag effect.
This package also includes the function N.APPLE
to back calculate the sample size given the power and hazard ratio,
and the function HR.APPLE
to back calculate the hazard ratio given
the power and sample size, respectively, using the close-form APPLE method.
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>
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.