| pow.APPLE | R Documentation |
Perform the power calculation using the close-form APPLE method based on the piecewise weighted log-rank test when the treatment time-lag effect is present and the lag duration is homogeneous across the individual subject
pow.APPLE(lambda1, t1, p, N, HR, tao, A, ap=0.5, alpha=0.05)
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. |
APPLE is an acronym for:
Analytic Power calculation method based on Piecewise weighted Log-rank tEst.
See the reference for details of this method.
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.
The power
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.
N.APPLE, HR.APPLE, pow.SEPPLE, pow.sim.logrk
lambda1 <- NULL
t1 <- 183
p <- 0.7
N <- 200
HR <- 0.55
tao <- 365*3
A <- 365
pow.APPLE(lambda1, t1, p, N, HR, tao, A)
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