Description Usage Arguments Value Examples

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.

1 2 | ```
AED3_SSR.sim(N1, rho, alpha, beta, theta, theta0, sigma0, pstar, nSim,
Seed)
``` |

`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 |

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

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
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)
``` |

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