AED.sim {esDesign}

Conduct the simulation studies of the Adaptive Enrichment Design without early stopping boundary

Description

The AED.sim() is used to conduct the simulation studies of the Adaptive Enrichment Design without early stopping boundary. The AED design is quite similar with the AED1_SSR design. But, in the AED design, the futility stopping boundary and the Sample Size Re-estimation Procedure are removed. On the contrary, a fixed sample size is used to replace the sample size re-estimated procedure. In addition, an \epsilon-rule is also introduced to select the subgroup with larger subgroup-specific test statistic.

Usage

AED.sim(
  N1,
  N2,
  rho,
  alpha,
  beta,
  theta,
  theta0,
  K,
  Info,
  epsilon,
  sigma0,
  nSim,
  Seed
)

Arguments

N1

The sample size used at the first stage

N2

The sample size used at the second stage

rho

The proportion of the subgroup 1

alpha

The overall Type I error rate

beta

The (1 - Power)

theta

The sizes of treatment effects in subgroups 1 and 2 among the experimental arm

theta0

The size of treatment effect in standard arm

K

The number of subgroups

Info

The observed information

epsilon

The threshold of difference between the subgroup-specific test statistics

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

• Enrich01 The prevalence of adaptive enrichment of subgroup 1

• Enrich02 The prevalence of adaptive enrichment of subgroup 2

References

• Lin, R., Yang, Z., Yuan, Y. and Yin, G., 2021. Sample size re-estimation in adaptive enrichment design. Contemporary Clinical Trials, 100, p.106216. <doi: 10.1016/j.cct.2020.106216>

Examples

N1 <- 310
N2 <- 310
rho <- 0.5
alpha <- 0.05
beta <- 0.20
theta <- c(0,0)
theta0 <- 0
K <- 2
Info <- 0.5
epsilon <- 0.5
sigma0 <- 1
nSim <- 1000
Seed <- 6
AED.sim(N1 = N1, N2 = N2, rho = rho, alpha = alpha,
        beta = beta, theta = theta, theta0 = theta0,
        K  = K, Info = Info, epsilon = epsilon,
        sigma0 = sigma0, nSim = nSim, Seed = Seed)