| DelayedEffect.Design {DelayedEffect.Design} | R Documentation |
Sample size and power calculations using the APPLE, SEPPLE, APPLE+ and SEPPLE+ methods
Description
An R package for sample size and power calculation when the treatment time-lag
effect is present. The package incorporates two specific lag assumptions:
1. the lag duration is homogeneous across the individual subject;
2. the lag duration varies heterogeneously from individual to individual within a
certain domain and following a specific pattern.
Details
The four 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),
3. Analytic Power calculation method based on generalized Piecewise weighted Log-rank tEst
with random treatment time-lag effect (APPLE+),
4. Simulation-based Empirical Power calculation method based on generalized Piecewise weighted
Log-rank tEst with random treatment time-lag effect (SEPPLE+).
See the reference for details of these methods.
Specifically, APPLE and SEPPLE assume that the lag duration is homogeneous across the individual subject,
whereas APPLE and SEPPLE assume that the lag duration varies heterogeneously from individual to individual
or from study to study within a certain domain and following a specific pattern.
The functions for computing power corresponding to the above methods are pow.APPLE, pow.SEPPLE, pow.APPLE.plus,
pow.SEPPLE.plus and pow.SEPPLE.random.DE. These can be compared to pow.sim.logrk and pow.sim.logrk.rankdom.DE
which compute the power from a simulation-based algorithm using the regular log-rank test which ignores the
existence of lag effects.
The package also includes the function N.APPLE, N.APPLE.plus to back calculate the sample size given the power
and hazard ratio, and the functions HR.APPLE and HR.APPLE.plus to back calculate the hazard ratio given the
power and sample size, respectively, using the close-from APPLE and APPLE+ methods.
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.