HR.APPLE {DelayedEffect.Design} | R Documentation |
APPLE hazard ratio computation
Description
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
Usage
HR.APPLE(lambda1, t1, p, N, tao, A, beta, ap=0.5, alpha=0.05)
Arguments
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. |
Details
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.
Value
The hazard ratio
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., 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
Examples
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)