Description Usage Arguments Value References Examples
The design function to sequentially monitor sample size and boundary based on Thall, Simon and Estey's criterion.
1 | MultPostP.design(type, nmax, a.vec, p0, theta, optimize)
|
type |
type of boundaries: "efficacy" or "futility" or "toxicity". |
nmax |
the maximum number of patients treated by the experimental drug. |
a.vec |
the hyperparameter vector of the Dirichlet prior for the experimental drug. |
p0 |
the prespecified reseponse rate for efficacy or toxicity. |
theta |
the cutoff probability: typically, θ = [0.9, 0.99] for efficacy, θ = [0.01, 0.1] for futility, and θ = [0.95, 1] for toxicity. |
optimize |
logical value, if optimize=TRUE, then only output the minimal sample size for the same number of futility boundaries and maximal sample size for the same number efficacy boundaries |
boundset |
the boundaries set: U_n or L_n for the experimental drug efficacy or futility; T_n for the experimental drug toxicity. |
Thall, Peter F., Richard M. Simon, and Elihu H. Estey. (1995). Bayesian sequential monitoring designs for single-arm clinical trials with multiple outcomes. Statistics in medicine 14.4: 357-379.
Yin, G. (2012). Clinical Trial Design: Bayesian and Frequentist Adaptive Methods. New York: Wiley.
1 2 3 4 | ## Using vague prior Unif(0,1)
MultPostP.design(type="futility",nmax = 30,a.vec = c(1,1,1,1),p0 = 0.15, theta = 0.05)
MultPostP.design(type="efficacy",nmax = 30,a.vec = c(1,1,1,1),p0 = 0.15, theta = 0.9)
MultPostP.design(type="toxicity",nmax = 30,a.vec = c(1,1,1,1),p0 = 0.15, theta = 0.95)
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Loading required package: animation
Loading required package: nleqslv
n bound
1 1 NA
2 2 NA
3 3 NA
4 4 NA
5 5 NA
6 6 NA
7 7 NA
8 8 NA
9 9 NA
10 10 NA
11 11 NA
12 12 NA
13 13 NA
14 14 NA
15 15 NA
16 16 NA
17 17 NA
18 18 NA
19 19 NA
20 20 NA
21 21 NA
22 22 NA
23 23 NA
24 24 NA
25 25 NA
26 26 NA
27 27 0
28 28 0
29 29 0
30 30 0
n bound
1 1 1
2 2 1
3 3 1
4 4 1
5 5 2
6 6 2
7 7 2
8 8 2
9 9 2
10 10 3
11 11 3
12 12 3
13 13 3
14 14 3
15 15 4
16 16 4
17 17 4
18 18 4
19 19 4
20 20 5
21 21 5
22 22 5
23 23 5
24 24 5
25 25 6
26 26 6
27 27 6
28 28 6
29 29 6
30 30 7
n bound
1 1 1
2 2 1
3 3 1
4 4 2
5 5 2
6 6 2
7 7 2
8 8 3
9 9 3
10 10 3
11 11 3
12 12 4
13 13 4
14 14 4
15 15 4
16 16 5
17 17 5
18 18 5
19 19 5
20 20 5
21 21 6
22 22 6
23 23 6
24 24 6
25 25 6
26 26 7
27 27 7
28 28 7
29 29 7
30 30 7
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