Description Usage Arguments References See Also Examples
Calculates the conditional error for all possible outcomes at the interim analysis (different number of responses) spending "rest alpha" (difference between nominal alpha level and actual alpha level) proportionally.
1  getD_proportionally(design, alpha)

design 
a dataframe containing all critical values for a Simon's twostage design defined by the colums "r1", "n1", "r", "n" and "p0".

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.
getD_equally
, getD_distributeToOne
, getD_none
1 2 3 4 5  #Calculate a Simon's twostage design
design < getSolutions()$Solutions[3,] #minimaxdesign for the default values.
ce_prop < getD_proportionally(design, 0.05)
ce_prop

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