find2stageDesigns {curtailment}

Find two-stage designs

Description

This function finds two-stage designs for a given set of design parameters, allowing stopping for benefit at the interim (Mander and Thompson's design) or no stopping for benefit at the interim (Simon's design). It returns not only the optimal and minimax design realisations, but all design realisations that could be considered "best" in terms of expected sample size under p=p0 (EssH0), expected sample size under p=p1 (Ess), maximum sample size (n) or any weighted combination of these three optimality criteria.

Usage

find2stageDesigns(
  nmin,
  nmax,
  p0,
  p1,
  alpha,
  power,
  maxthetaF = NA,
  benefit = FALSE
)

Arguments

nmin

Minimum permitted sample size. Should be a multiple of block size or number of stages.

nmax

Maximum permitted sample size. Should be a multiple of block size or number of stages.

p0

Probability for which to control the type-I error-rate

p1

Probability for which to control the power

alpha

Significance level

power

Required power (1-beta)

maxthetaF

Maximum permitted conditional power for futility stopping. Optional.

benefit

Allow the trial to end for a go decision and reject the null hypothesis at the interim analysis (i.e., the design of Mander and Thompson)

Value

A list of class "curtailment_simon" containing two data frames. The first data frame, $input, has a single row and contains all the inputted values. The second data frame, $all.des, contains one row for each design realisation, and contains the details of each design, including sample size, stopping boundaries and operating characteristics. To see a diagram of any obtained design realisation and its corresponding stopping boundaries, simply call the function drawDiagram with this output as the only argument.

Author(s)

Martin Law, [e-mail]

References

doi:10.1016/j.cct.2010.07.008A.P. Mander, S.G. Thompson, Two-stage designs optimal under the alternative hypothesis for phase II cancer clinical trials, Contemporary Clinical Trials, Volume 31, Issue 6, 2010, Pages 572-578

doi:10.1016/0197-2456(89)90015-9Richard Simon, Optimal two-stage designs for phase II clinical trials, Controlled Clinical Trials, Volume 10, Issue 1, 1989, Pages 1-10

Examples

find2stageDesigns(nmin=23,
 nmax=27,
 p0=0.75,
 p1=0.92,
 alpha=0.22,
 power=0.95,
 benefit=TRUE)