Calculates Optimal and Minimax 2-stage Phase II designs given by Richard Simon
ph2simon(pu, pa, ep1, ep2, nmax=100)
# S3 method for ph2simon
print(x, ...)
# S3 method for ph2simon
plot(x, ...)ph2simon returns a list with pu, pa, alpha, beta and nmax as above and:
matrix of best 2 stage designs for each value of total sample size n. The 6 columns in the matrix are:
| r1 | number of responses needed to exceeded in first stage |
| n1 | number of subjects treated in first stage |
| r | number of responses needed to exceeded at the end of trial |
| n | total number of subjects to be treated in the trial |
| EN(pu) | expected number pf patients in the trial under pu |
| PET(pu) | probability of stopping after the first stage under pu |
Trial is stopped early if <= r1 responses are seen in the first stage and treatment is considered desirable only when >r responses seen.
unacceptable response rate; baseline response rate that needs to be exceeded for treatment to be deemed promising
response rate that is desirable; should be larger than pu
threshold for the probability of declaring drug desirable under pu (target type 1 error rate); between 0 and 1
threshold for the probability of rejecting the drug under pa (target type 2 error rate); between 0 and 1
maximum total sample size (default 100; can be at most 1000)
object returned by ph2simon
arguments to be passed onto plot and print commands called within
print(ph2simon): formats and returns the minimax,
optimal and any admissible designs.
plot(ph2simon): plots the expected sample size against
the maximum sample size as in Jung et al., 2001
Simon R. (1989). Optimal Two-Stage Designs for Phase II Clinical Trials. Controlled Clinical Trials 10, 1-10.
Jung SH, Carey M and Kim KM. (2001). Graphical Search for Two-Stage Designs for Phase II Clinical Trials. Controlled Clinical Trials 22, 367-372.
twostage.inference, oc.twostage.bdry
ph2simon(0.2, 0.4, 0.1, 0.1)
ph2simon(0.2, 0.35, 0.05, 0.05)
ph2simon(0.2, 0.35, 0.05, 0.05, nmax=150)
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