OneArmPhaseTwoStudy (version 1.0.3)

getSolutionsSub1: Calculates designs for a given "sub1"-object.

Description

By iterating over all possible values for "r1", "n1", "r", "s" and "n" designs for a given "sub1"-object are found. Proceeding to the second stage of the study more than "r1" responses among the first "n1" patients in the subset endpoint are needed. Rejecting the null hypothesis more than "r" responses in the subset endpoint or more than "s" responses in the superset endpoint among "n" patients are needed.

Usage

getSolutionsSub1(sub1 = setupSub1Design(), skipS = TRUE, skipR = TRUE,
  skipN1 = TRUE, lowerBorder = 0, upperBorder = 0,
  useCurtailment = FALSE, curtailAll = FALSE, cut = 0,
  replications = 1000)

Arguments

sub1

a "sub1"-object which will be used to calculate fitting designs

skipS

boolean value; skips the iteration over "s" at certian points to improve calculation speed (finds less designs)

skipR

boolean value; skips the iteration over "r" at certian points to improve calculation speed (finds less designs)

skipN1

boolean value; skips the iteration over "n1" at certian points to improve calculation speed (finds less designs and it is impossible to determine the optimalization criteria of the found designs)

lowerBorder

sets a minimal value for "n" (number of patients to be recruited)

upperBorder

sets a maximal value for "n" (number of patients to be recruited)

useCurtailment

determines if the effect of (non-)stochastic curtailment should also be calculated for the found designs

curtailAll

boolean value; if true the effect of (non-)stochastic curtailment will be calculated for different cut points in 0.05 steps starting with the value of the parameter "cut".

cut

sets the "cut point" used to calculate the effect of (non-)stochastic curtailment. A study is stopped if the conditional power falls below the value of "cut".

replications

number of simulations to estimate the effect of (non-)stochastic curtailment.

References

Kunz C.U., Kieser M (2012): Curtailment in single-arm two-stage phase II oncology trials. Biometrical Journal 54, 445-456

See Also

setupSub1Design

Examples

# NOT RUN {
# Example 1: Using the default values
sub1 <- setupSub1Design()
getSolutionsSub1(sub1)
# }
# NOT RUN {
# Example 2: Setting up a "sub1"-object, then calculating designs
sub1 <- setupSub1Design(alpha = 0.1, beta = 0.2, pc0 = 0.3, pt0 = 0.4)
designs <- getSolutionsSub1(sub1)$Solutions
designs

# Example 2: Calculating designs and simulating the influence of stochastic curtailment
# for each design.
sub1 <- setupSub1Design(alpha = 0.1, beta = 0.2, pc0 = 0.3, pt0 = 0.4)
designs <- getSolutionsSub1(sub1, useCurtailment = TRUE, curtailAll = TRUE, cut = 0.3)
#Contains the found designs, the influence of stochastic curtailment
#and the regarding stopping rules .
designs
# }