esDesign (version 1.0.3)

AED3_SSR.sim: Conduct the simulation studies of the Adaptive Enrichment Design (Strategy 3) with Sample Size Re-estimation Procedure based on Futility and Efficacy Stopping Boundaries for the continuous endpoint

Description

The AED3_SSR.sim() is used to conduct the adaptive enrichment design with Sample Size Re-estimation, in which futility and efficacy stopping boundaries are used to guide the adaptive enrichment process. For the adaptively enriched subgroup, we re-estimate the sample size to maintain an adequate conditional power meanwhile protect the overall Type I error rate.

Usage

AED3_SSR.sim(N1, rho, alpha, beta, theta, theta0, sigma0, pstar, nSim, Seed)

Arguments

N1

The sample size used at the first stage

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 experimental treatment

theta0

The size of treatment effect in standard treatment

sigma0

The known variance of the treatment effect

pstar

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

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

• Trigger03 The prevalence of early stopping for the situation, in which the treatment effect in subgroup 1 is superiority, while the treatment effect in subgroup 2 is inconclusive

• Trigger04 The prevalence of early stopping for the situation, in which the treatment effect in subgroup 2 is superiority, while the treatment effect in subgroup 2 is inconclusive

• ESF The probability of early stopping for futility

• ESE The probability of early stopping for efficacy

Examples

# NOT RUN {
N <- 310
rho <- 0.5
alpha <- 0.05
beta <- 0.2
theta <- c(0,0)
theta0 <- 0
sigma0 <- 1
pstar <- 0.20
nSim <- 100
Seed <- 6
res <- AED3_SSR.sim(N1 = N, rho = rho, alpha = alpha,
             beta = beta, theta = theta, theta0 = theta0,
             sigma0 = sigma0, pstar = pstar, nSim = nSim,
             Seed = Seed)
# }