IUT.design: The design function for multinomial designs under...

In ph2mult: Phase II Clinical Trial Design for Multinomial Endpoints

Description

Search the type I error or power of a multinomial (response and disease progression) single- or two-stage design under IUT: H_0: p_1 ≤ p_{01} \ OR \ p_2 ≥ p_{02} \ versus \ H_1: p_1 ≥ p_{11} > p_{01} \ AND \ p_2 ≤ p_{12} < p_{02}

Usage

IUT.design(method = c("s1", "s2", "s2.f"),
s1.rej, t1.rej, s1.acc, t1.acc, n1, s2.rej, t2.rej, n2,
s1.rej.delta=0, t1.rej.delta=0, s1.acc.delta=0, t1.acc.delta=0,
s2.rej.delta=0, t2.rej.delta=0, n1.delta=0, n2.delta=0,
p0.s, p0.t, p1.s, p1.t, signif.level = 0.05, power.level = 0.85,
show.time = TRUE, output = c("minimax","optimal","maxpower","admissible", "all"),
plot.out=FALSE)

Arguments

method	design methods according to number of stage and stopping rule, "s1" represents single-stage design stopping for both efficacy and futility, "s2" represents two-stage design stopping for both efficacy and futility, "s2.f" represents two-stage design stopping for futility only.
s1.rej	first stage responses threshold to stop the trial for efficacy. Applied for "s1" or "s2".
t1.rej	first stage disease progressions threshold to stop the trial for efficacy. Applied for "s1" or "s2".
s1.acc	first stage responses threshold to stop the trial for futility. Applied for "s2" or "s2.f".
t1.acc	first stage disease progressions threshold to stop the trial for futility. Applied for "s2" or "s2.f".
n1	first stage sample size. Applied for "s1", "s2" or "s2.f".
s2.rej	second stage responses threshold to stop the trial for efficacy. Applied for "s2" or "s2.f".
t2.rej	second stage disease progressions threshold to stop the trial for efficacy. Applied for "s2" or "s2.f".
n2	second stage sample size. Applied for "s2" or "s2.f".
s1.rej.delta	pre-specified search difference for s1.rej.
t1.rej.delta	pre-specified search difference for t1.rej.
s1.acc.delta	pre-specified search difference for s1.acc.
t1.acc.delta	pre-specified search difference for t1.acc.
s2.rej.delta	pre-specified search difference for s2.rej.
t2.rej.delta	pre-specified search difference for t2.rej.
n1.delta	pre-specified search difference for n1.
n2.delta	pre-specified search difference for n2.
p0.s	pre-specified response rate under null hypothesis.
p0.t	pre-specified disease progression rate under null hypothesis.
p1.s	pre-specified response rate under alternative hypothesis.
p1.t	pre-specified disease progression rate under alternative hypothesis. Note: type I error calculation needs to take maximum of the power function with (p.s,p.t)=(p_{01},0) and (p.s,p.t)=(1-p_{02},p_{02})
signif.level	pre-specified significant level.
power.level	pre-specified power level.
show.time	logical; if TRUE (default), show the calculation time for the search function.
output	the output types of design, choose from "minimax","optimal","admissible" and "maxpower".
plot.out	logical; if TRUE, output a plot for design selection.

Value

boundset

the boundaries set satisfying the design types properties: s.rej, t.rej and N for "s1", s1.rej, t1.rej, s1.acc, t1.acc and N1 for first stage and s2.rej, t2.rej and N2 for the second stage of "s2", s1.acc, t1.acc and N1 for first stage and s2.rej, t2.rej and N2 for the second stage of "s2.f",

References

Chang, M. N., Devidas, M., & Anderson, J. (2007). One- and two-stage designs for phase II window studies. Statistics in medicine , 26(13), 2604-2614.

Simon, R. (1989). Optimal two-stage designs for phase II clinical trials. Controlled clinical trials 10(1), 1-10.

Jung, S. H., Lee, T., Kim, K., & George, S. L. (2004). Admissible two-stage designs for phase II cancer clinical trials. Statistics in medicine 23(4), 561-569.

Examples

p01=0.1; p02=0.9
## Calculate type I error for single-stage design
IUT.design(method="s1",s1.rej=18, t1.rej = 12, n1=80,
s1.rej.delta = 1, t1.rej.delta = 1, n1.delta=1,
p0.s = 0.15, p0.t = 0.25, p1.s = 0.3, p1.t= 0.1, output = "minimax")

## Designs for two-stage design, output PET and EN under null hypothesis
IUT.design(method="s2",s1.rej = 11, t1.rej = 4, s1.acc=8, t1.acc = 5, n1=40,
s2.rej=18, t2.rej = 11, n2=40, p0.s = 0.15, p0.t = 0.25, p1.s = 0.3, p1.t= 0.1, output = "minimax")
IUT.design(method="s2",s1.rej = 11, t1.rej = 4, s1.acc=8, t1.acc = 5, n1=40,
s2.rej=18, t2.rej = 11, n2=40, p0.s = 0.15, p0.t = 0.25, p1.s = 0.3, p1.t= 0.1, output = "optimal")

ph2mult documentation built on May 2, 2019, 1:46 p.m.