MaST.sim: Conduct the simulation studies of the Marker Sequential Test...

In esDesign: Adaptive Enrichment Designs with Sample Size Re-Estimation

Description

The MaST.sim() is used to conduct the simulation studies of the marker sequential test design (MaST).

Usage

MaST.sim(N, rho, alpha, beta, theta, theta0, sigma0, nSim, Seed)

Arguments

N	The total sample size used at the trial
rho	The proportion of subgroup 1 among the overall patients
alpha	The overall Type I error rate
beta	The (1 - Power)
theta	The sizes of treatment effect in subgroups 1 and 2 with the experimental arm
theta0	The size of treatment effect in the standard arm
sigma0	The variance of the treatment effect
nSim	The number of simulated studies
Seed	The random seed

Value

A list contains

• nTotal The average expected sample size

• H00 The probability of rejecting the null hypothesis of H_{00}

• H01 The probability of rejecting the null hypothesis of H_{01}

• H02 The probability of rejecting the null hypothesis of H_{02}

• H0 The probabilities of rejecting at least one of the null hypothesis

References

• Freidlin, B., Korn, E. L., and Gray, R. (2014). Marker sequential test (MaST) design. Clinical trials, 11(1), 19-27. <doi:10.1177/1740774513503739>

Examples

N <- 310
rho <- 0.5
alpha <- 0.05
beta <- 0.20
theta <- c(0,0)
theta0 <- 0
sigma0 <- 1
nSim <- 1000
Seed <- 6
MaST.sim(N = N, rho = rho, alpha = alpha, beta = beta,
         theta = theta, theta0 = theta0, sigma0 = sigma0,
         nSim = nSim, Seed = Seed)

esDesign documentation built on July 13, 2021, 9:06 a.m.