CalculateSimonDsgn: Simon's designs

In arsenionhacolo/InferenceBEAGSD: Inference for Binary Endpoint Adaptive Group-Sequential Designs

Description

CalculateSimonDsgn finds Simon's optimal and minimax designs.

Usage

CalculateSimonDsgn(p0, p1, alpha, beta, verbose = TRUE)

Arguments

p0	The response rate under the null hypothesis.
p1	The response rate under the alternative hypothesis.
alpha	Type I error rate.
beta	Type II error rate.
verbose	If TRUE (default) the designs are printed (gives messy printout when the function is run without assigment).

Details

Simon's designs are two-stage single-arm for phase II clinical trials. They consist in first stage and overall sample sizes and critical values, n1 and n, and r1 and r, respectively.

Value

A two-row dataframe containing the optimal and the minimax designs.

Author(s)

Arsenio Nhacolo

References

Simon, R. Optimal two-stage designs for phase II clinical trials. Control Clin Trials, 1989, 10, 1-10.

See Also

SimulateSimonDsgn and SimulateSimonDsgnAdaptN.

Examples

d <- CalculateSimonDsgn(0.2, 0.4, 0.05, 0.1)

arsenionhacolo/InferenceBEAGSD documentation built on May 9, 2019, 4:10 a.m.