AED3_SSR.sim {esDesign} | R Documentation |
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 |
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 |
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
H01 The probability of rejecting the null hypothesis of
H02 The probability of rejecting the null hypothesis of
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
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)