Unified Interface for Two Co-Primary Binary Endpoints (Approximate Methods)

This function provides a unified interface for both power calculation and sample size determination for two co-primary binary endpoints using asymptotic normal approximation methods.

Usage

twoCoprimary2BinaryApprox(
  n1 = NULL,
  n2 = NULL,
  p11,
  p12,
  p21,
  p22,
  rho1,
  rho2,
  power = NULL,
  r = NULL,
  alpha = 0.025,
  Test = "AN"
)

Arguments

n1: Sample size for group 1 (treatment group). If NULL, will be calculated.
n2: Sample size for group 2 (control group). If NULL, will be calculated.
p11: True response probability for endpoint 1 in group 1
p12: True response probability for endpoint 2 in group 1
p21: True response probability for endpoint 1 in group 2
p22: True response probability for endpoint 2 in group 2
rho1: Correlation between endpoints 1 and 2 in group 1
rho2: Correlation between endpoints 1 and 2 in group 2
power: Target power (1 - beta). If NULL, will be calculated.
r: Allocation ratio (n1/n2). Required when calculating sample size.
alpha: One-sided significance level (typically 0.025 or 0.05)
Test: Test method: "AN" (asymptotic normal), "ANc" (with continuity correction), "AS" (arcsine), or "ASc" (arcsine with continuity correction)

Value

An object of class "twoCoprimary" containing either:

Power calculation results (when n1 and n2 are specified)
Sample size calculation results (when power and r are specified)

Details

This function serves as a unified interface similar to power.prop.test(). The function determines the operation mode based on which parameters are NULL.

Exactly one of {(n1, n2), (power, r)} must be NULL.

Examples

# Calculate power given sample sizes
twoCoprimary2BinaryApprox(
  n1 = 200, n2 = 100,
  p11 = 0.5, p12 = 0.4,
  p21 = 0.3, p22 = 0.2,
  rho1 = 0.7, rho2 = 0.7,
  alpha = 0.025, Test = "AN"
)
#> 
#> Power calculation for two binary co-primary endpoints
#> 
#>              n1 = 200
#>              n2 = 100
#>     p (group 1) = 0.5, 0.4
#>     p (group 2) = 0.3, 0.2
#>             rho = 0.7, 0.7
#>           alpha = 0.025
#>            Test = AN
#>          power1 = 0.91929
#>          power2 = 0.949617
#>  powerCoprimary = 0.894946
#> 

# Calculate sample size given target power
twoCoprimary2BinaryApprox(
  p11 = 0.5, p12 = 0.4,
  p21 = 0.3, p22 = 0.2,
  rho1 = 0.7, rho2 = 0.7,
  power = 0.8, r = 1,
  alpha = 0.025, Test = "AN"
)
#> 
#> Sample size calculation for two binary co-primary endpoints
#> 
#>              n1 = 105
#>              n2 = 105
#>               N = 210
#>     p (group 1) = 0.5, 0.4
#>     p (group 2) = 0.3, 0.2
#>             rho = 0.7, 0.7
#>      allocation = 1
#>           alpha = 0.025
#>            beta = 0.2
#>            Test = AN
#>