Type: Package
Title: Calculate Sample Size for Single-Arm Survival Studies
Version: 0.1.0
Description: Provides methods to calculate sample size for single-arm survival studies using the arcsine transformation, incorporating uniform accrual and exponential survival assumptions. Includes functionality for detailed numerical integration and simulation. This method is based on Nagashima et al. (2021) <doi:10.1002/pst.2090>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.2.3
Imports: stats
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, devtools
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-01-13 20:00:05 UTC; moko
Author: Mohamed Kamal [aut, cre]
Maintainer: Mohamed Kamal <mohamedkamalhospital@gmail.com>
Repository: CRAN
Date/Publication: 2025-01-15 10:20:02 UTC

Calculate Sample Size Using Arcsine Transformation

Description

This function calculates the required sample size for single-arm survival studies based on the arcsine transformation method. It accounts for uniform accrual and exponential survival assumptions, including numeric integration for time points that exceed the follow-up period.

Usage

calcSampleSizeArcsine(
  S0,
  S1,
  alpha = 0.05,
  power = 0.8,
  accrual = 24,
  followup = 24,
  timePoint = 18,
  steps = 10000
)

Arguments

S0

Numeric. Survival probability under the null hypothesis (must be strictly between 0 and 1).

S1

Numeric. Survival probability under the alternative hypothesis (must be strictly between 0 and 1).

alpha

Numeric. The one-sided Type I error rate. Default is 0.05.

power

Numeric. Desired statistical power of the test (1 - beta). Default is 0.80.

accrual

Numeric. Duration of the accrual period in months. Default is 24.

followup

Numeric. Additional follow-up duration in months after accrual. Default is 24.

timePoint

Numeric. Time of interest in months for evaluating survival probabilities. Default is 18.

steps

Integer. Number of steps for numeric integration if timePoint exceeds follow-up duration. Default is 10,000.

Value

Integer. The required sample size, rounded up to the nearest whole number.

Examples

# Calculate sample size for typical survival probabilities
calcSampleSizeArcsine(S0 = 0.90, S1 = 0.96)

# Adjusting for lower survival probabilities and extended accrual
calcSampleSizeArcsine(
  S0 = 0.80,
  S1 = 0.85,
  accrual = 36,
  followup = 12,
  timePoint = 24
)