esDesign (version 1.0.3)

AED2_SSR.sim: Conduct the simulation studies of the Adaptive Enrichment Design (Strategy 2) with Sample Size Re-estimation Procedure

Description

The AED2_SSR.sim() is used to conduct the simulation studies of the Adaptive Enrichment Design (Strategy) with sample size re-estimation procedure. The AED2-SSR is different from the AED3-SSR, in which an \(\epsilon\)-rule is introduced to select the subgroup with larger subgroup-specific test statistic.

Usage

AED2_SSR.sim(
  N1,
  rho,
  alpha,
  beta,
  pstar,
  theta,
  theta0,
  sigma0,
  epsilon,
  nSim,
  Seed
)

Arguments

N1

The sample size used in the first stage

rho

The proportion of subgroup 1

alpha

The overall Type I error rate

beta

The (1 - power)

pstar

The (1 - power) of accepting the null hypothesis at the interim analysis.

theta

The sizes of treatment effect in subgroups 1 and 2 with the experimental treatment

theta0

The size of treatment effect with the standard treatment

sigma0

The variance of the treatment effect

epsilon

The threshold of the difference between subgroup-specific test statistics

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

• ESF The probability of early stopping for futility

• ESE The probability of early stopping for efficacy

• Enrich01 The prevalence of adaptive enrichment of subgroup 1

• Enrich02 The prevalence of adaptive enrichment of subgroup 2

• Trigger03 The prevalence of no enrichment

Examples

# NOT RUN {
N <- 310
rho <- 0.5
alpha <- 0.05
beta <- 0.2
theta <- c(0,0)
theta0 <- 0
sigma0 <- 1
epsilon <- 0.5
pstar <- 0.20
nSim <- 1000
Seed <- 6
res <- AED2_SSR.sim(N1 = N, rho = rho, alpha = alpha,
             beta = beta, theta = theta, theta0 = theta0,
             sigma0 = sigma0, pstar = pstar, epsilon = epsilon,
             nSim = nSim, Seed = Seed)
# }