Description Usage Arguments Value Author(s) References Examples
Calculates Optimal 2-stage Phase II designs given by Deepak Parashar (2016).
1 | design.parashar(alpha=0.05,beta=0.2,p0,p1n,p1p,Nmax=100,NumThreads=1)
|
alpha |
Type I error. |
beta |
Type II error. |
p0 |
Max unacceptable response rate. |
p1n |
Min acceptable response rate for "negative" subgroup. |
p1p |
Min acceptable response rate for "positive" subgroup. |
Nmax |
Maximum sample size. |
NumThreads |
Number of threads used for parallel compilation. |
Returns a data.frame object which components are :
alpha |
Type I error probability of the optimal design. |
power |
Power of the optimal design. |
p0 |
Max unacceptable response rate. |
p1n |
Min acceptable response rate for "negative" subgroup. |
p1p |
Min acceptable response rate for "positive" subgroup. |
PET |
Overall probability of early termination. |
EN |
Expected sample size. |
k1n |
Minimum number of responses in marker negative subjects to go into the unselected population during stage 2. |
k1p |
Minimum number of responses in the marker positive subjects. |
N1n |
Number of marker negative subjects enrolled during the first stage. |
N1p |
Number of marker positive subjects enrolled during the first stage. |
kep |
Minimum number of responses in the enrichment population. |
Nep |
Number of subjects in the enrichment population. |
kn |
Total number of response required during stage 1 and stage 2 combined in the negative sample to conclude efficacy in the unselected population. |
kp |
Total number of response required during stage 1 and stage 2 combined in the amplified sample to conclude efficacy in this population when preliminary efficacy is unselected. |
Nn |
Number of marker negative subjects enrolled during the first stage and the second stage. |
N2p |
Number of marker positive subjects enrolled during the first stage and the second stage. |
Patrick Sfumato and Bastien Cabarrou.
Parashar D, Bowden J, Starr C, Wernisch L and Mander A (2016).An optimal stratified Simon two-stage design. Pharmaceutical statistics 15(4) 333-40.
1 2 3 4 5 6 | out.parashar<-design.parashar(alpha=0.05,
beta=0.2,
p0=0.03,
p1n=0.25,
p1p=0.40,
Nmax=30)
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