BinarySampleSize {bbssr}R Documentation

Sample Size Calculation for Two-Arm Trials with Binary Endpoints

Description

Calculates the required sample size for two-arm trials with binary endpoints using various exact statistical tests. The function supports five different one-sided tests.

Usage

BinarySampleSize(p1, p2, r, alpha, tar.power, Test)

Arguments

p1

True probability of responders for group 1

p2

True probability of responders for group 2

r

Allocation ratio to group 1 (i.e., allocation ratio of group 1:group 2 = r:1, r > 0)

alpha

One-sided level of significance

tar.power

Target power

Test

Type of statistical test. Options: 'Chisq', 'Fisher', 'Fisher-midP', 'Z-pool', or 'Boschloo'

Details

The function supports the following five one-sided tests:

The calculation uses a three-step approach:

  1. Calculate initial sample size using normal approximation for chi-squared test

  2. Perform power calculation with the initial sample size

  3. Use grid search algorithm to find the optimal sample size

Value

A data frame containing:

p1

True probability of responders for group 1

p2

True probability of responders for group 2

r

Allocation ratio to group 1

alpha

One-sided level of significance

tar.power

Target power

Test

Name of the statistical test

Power

Calculated power

N1

Required sample size of group 1

N2

Required sample size of group 2

N

Total required sample size

Author(s)

Gosuke Homma (my.name.is.gosuke@gmail.com)

Examples

# Simple sample size calculation with fast Chi-squared test
result1 <- BinarySampleSize(p1 = 0.4, p2 = 0.2, r = 1, alpha = 0.025,
                           tar.power = 0.8, Test = 'Chisq')
print(result1)


# More computationally intensive examples
# Sample size for Fisher exact test
result2 <- BinarySampleSize(p1 = 0.5, p2 = 0.2, r = 2, alpha = 0.025,
                           tar.power = 0.9, Test = 'Fisher')
print(result2)

# Sample size for Boschloo test
result3 <- BinarySampleSize(p1 = 0.6, p2 = 0.3, r = 1, alpha = 0.025,
                           tar.power = 0.8, Test = 'Boschloo')
print(result3)



[Package bbssr version 1.0.2 Index]