Unified Interface for Mixed Continuous and Binary Co-Primary Endpoints

This function provides a unified interface for both power calculation and sample size determination for trials with one continuous and one binary co-primary endpoint.

Usage

twoCoprimary2MixedContinuousBinary(
  n1 = NULL,
  n2 = NULL,
  delta,
  sd,
  p1,
  p2,
  rho,
  power = NULL,
  r = NULL,
  alpha = 0.025,
  Test = "AN",
  nMC = 10000
)

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.

delta

Mean difference for the continuous endpoint

sd

Common standard deviation for the continuous endpoint

p1

True response probability for the binary endpoint in group 1

p2

True response probability for the binary endpoint in group 2

rho

Biserial correlation between the continuous endpoint and the latent continuous variable underlying the binary endpoint

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 for the binary endpoint: "AN" (asymptotic normal), "ANc" (with continuity correction), "AS" (arcsine), "ASc" (arcsine with continuity correction), or "Fisher" (Fisher's exact test)

nMC

Number of Monte Carlo simulations when Test = "Fisher". Default is 10000.

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.

The biserial correlation rho represents the correlation between the observed continuous endpoint and the latent continuous variable underlying the binary endpoint.

Examples

# Calculate power given sample sizes
twoCoprimary2MixedContinuousBinary(
  n1 = 100, n2 = 100,
  delta = 0.5, sd = 1,
  p1 = 0.6, p2 = 0.4,
  rho = 0.5,
  alpha = 0.025, Test = "AN"
)
#> 
#> Power calculation for mixed continuous and binary co-primary endpoints
#> 
#>              n1 = 100
#>              n2 = 100
#>           delta = 0.5
#>              sd = 1
#>               p = 0.6, 0.4
#>             rho = 0.5
#>           alpha = 0.025
#>            Test = AN
#>       powerCont = 0.942438
#>        powerBin = 0.812291
#>  powerCoprimary = 0.781111
#> 

# Calculate sample size given target power
twoCoprimary2MixedContinuousBinary(
  delta = 0.5, sd = 1,
  p1 = 0.6, p2 = 0.4,
  rho = 0.5,
  power = 0.8, r = 1,
  alpha = 0.025, Test = "AN"
)
#> 
#> Sample size calculation for mixed continuous and binary co-primary endpoints
#> 
#>              n1 = 105
#>              n2 = 105
#>               N = 210
#>           delta = 0.5
#>              sd = 1
#>               p = 0.6, 0.4
#>             rho = 0.5
#>      allocation = 1
#>           alpha = 0.025
#>            beta = 0.2
#>            Test = AN
#>