| HR.APPLE | R Documentation |
Perform the post-delay hazard ratio calculation given power and sample size 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
HR.APPLE(lambda1, t1, p, N, tao, A, beta, 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 |
tao |
Total study duration |
A |
Total enrollment duration |
beta |
Type II error rate; Power=1-beta |
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 hazard ratio
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.
pow.APPLE, N.APPLE
lambda1 <- NULL
t1 <- 183
p <- 0.7
N <- 200
tao <- 365*3
A <- 365
beta <- 0.2
HR.APPLE(lambda1, t1, p, N, tao, A, beta)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.