Description Usage Arguments References Examples
Calculates the number of patients which should be enrolled in the second stage if the conditional power should be altert to "cp".
1 |
cp |
conditional power to which the number of patients for the second stage should be adjusted. |
p1 |
response probability under the alternative hypothesis. |
design |
a dataframe containing all critical values for a Simon's two-stage design defined by the colums r1, n1, r, n and p0.
|
k |
number of responses observed at the interim analysis. |
mode |
a value out of {0,1,2,3} dedicating the methode spending the "rest alpha" (difference between nominal alpha level and actual alpha level for the given design).
|
alpha |
overall significance level the trial was planned for. |
Englert S., Kieser M. (2012): Adaptive designs for single-arm phase II trials in oncology. Pharmaceutical Statistics 11,241-249.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | #Calculate a Simon's two-stage design
design <- getSolutions()$Solutions[3,] #minimax-design for the default values.
#Assume we only observed 3 responses in the interim analysis.
#Therefore the conditional power is only about 0.55.
#In order to raise the conditional power to 0.8 "n2" has to be increased.
#set k to 3 (only 3 responses observed so far)
k = 3
# Assume we spent the "rest alpha" proportionally in the planning phase
# there for we set "mode = 1".
n2 <- getN2(cp = 0.8, design$p1, design, k, mode = 1, alpha = 0.05)
n2
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