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 twostage 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 singlearm phase II trials in oncology. Pharmaceutical Statistics 11,241249.
1 2 3 4 5 6 7 8 9 10 11 12 13 14  #Calculate a Simon's twostage design
design < getSolutions()$Solutions[3,] #minimaxdesign for the default values.
#Assume we only observed 3 responses in the interim analysis.
#Therefore the conditional power is only about 0.55.
#In order to raise the conditional power to 0.8 "n2" has to be increased.
#set k to 3 (only 3 responses observed so far)
k = 3
# Assume we spent the "rest alpha" proportionally in the planning phase
# there for we set "mode = 1".
n2 < getN2(cp = 0.8, design$p1, design, k, mode = 1, alpha = 0.05)
n2

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