# 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 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. ```r 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 ## Returns 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 ```r 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) ```

AED3_SSR.sim function