npsurvSS: Sample Size and Power Calculation for Common Non-Parametric Tests in Survival Analysis

A number of statistical tests have been proposed to compare two survival curves, including the difference in (or ratio of) t-year survival, difference in (or ratio of) p-th percentile survival, difference in (or ratio of) restricted mean survival time, and the weighted log-rank test. Despite the multitude of options, the convention in survival studies is to assume proportional hazards and to use the unweighted log-rank test for design and analysis. This package provides sample size and power calculation for all of the above statistical tests with allowance for flexible accrual, censoring, and survival (eg. Weibull, piecewise-exponential, mixture cure). It is the companion R package to the paper by Yung and Liu (2020) <doi:10.1111/biom.13196>. Specific to the weighted log-rank test, users may specify which approximations they wish to use to estimate the large-sample mean and variance. The default option has been shown to provide substantial improvement over the conventional sample size and power equations based on Schoenfeld (1981) <doi:10.1093/biomet/68.1.316>.

Version: 1.1.0
Depends: R (≥ 3.4.0)
Imports: stats, utils
Suggests: knitr, rmarkdown, dplyr, tidyr, tibble, ggplot2
Published: 2024-05-08
DOI: 10.32614/CRAN.package.npsurvSS
Author: Godwin Yung [aut, cre], Yi Liu [aut]
Maintainer: Godwin Yung <godwin.y.yung at>
License: GPL-2
NeedsCompilation: no
CRAN checks: npsurvSS results


Reference manual: npsurvSS.pdf
Vignettes: Basic functionalities
Example 1: Optimal randomization ratio
Example 2: Delayed treatment effect


Package source: npsurvSS_1.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): npsurvSS_1.1.0.tgz, r-oldrel (arm64): npsurvSS_1.1.0.tgz, r-release (x86_64): npsurvSS_1.1.0.tgz, r-oldrel (x86_64): npsurvSS_1.1.0.tgz
Old sources: npsurvSS archive

Reverse dependencies:

Reverse imports: gsDesign2


Please use the canonical form to link to this page.