BinaryPower {bbssr}R Documentation

Power Calculation for Two-Arm Trials with Binary Endpoints

Description

Calculates power for two-arm trials with binary endpoints using exact statistical tests. The function supports five different one-sided tests and can handle vectors of probabilities.

Usage

BinaryPower(p1, p2, N1, N2, alpha, Test)

Arguments

p1

True probability of responders for group 1 (can be a vector with different values)

p2

True probability of responders for group 2 (can be a vector with different values)

N1

Sample size for group 1

N2

Sample size for group 2

alpha

One-sided level of significance

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 power calculation is based on the exact distribution of the test statistic under the specified alternative hypothesis.

Value

A numeric value or vector of power values. If vectors are provided for p1 and p2, a vector of powers corresponding to each combination will be returned.

Author(s)

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

Examples

# Simple power calculation with fast Chi-squared test
power1 <- BinaryPower(p1 = 0.5, p2 = 0.2, N1 = 5, N2 = 5,
                     alpha = 0.025, Test = 'Chisq')
print(power1)


# More computationally intensive examples
# Single power calculation with larger sample size
power2 <- BinaryPower(p1 = 0.5, p2 = 0.2, N1 = 10, N2 = 40,
                     alpha = 0.025, Test = 'Boschloo')
print(power2)

# Multiple power calculations
p1_vec <- c(0.5, 0.6, 0.7, 0.8)
p2_vec <- c(0.2, 0.2, 0.2, 0.2)
powers <- BinaryPower(p1 = p1_vec, p2 = p2_vec, N1 = 10, N2 = 40,
                     alpha = 0.025, Test = 'Fisher')
print(powers)



[Package bbssr version 1.0.2 Index]