getCP {OneArmPhaseTwoStudy} | R Documentation |
Calculates the conditional power for a given Simon's two-stage design in the interim analysis if the number of patients which should be enrolled in the second stage is altert to "n2".
getCP(n2, p1, design, k, mode = 0, alpha = 0.05)
n2 |
number of patients to be enrolled in the second stage of the study. |
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.
#Calculate a Simon's two-stage design design <- getSolutions()$Solutions[3,] #minimax-design for the default values. #Assume 3 responses were observed in the interim analysis. #Therefore the conditional power is only about 0.55. #In order to raise the conditional power to 0.8 "n2" has to be increased. #get the current "n2" n2 <- design$n - design$n1 #set k to 3 (only 3 responses observed so far) k = 3 #get the current conditional power cp <- getCP(n2, design$p1, design, k, mode = 1, alpha = 0.05) cp #increase n2 until the conditional power is larger than 0.8 while(cp < 0.8){ n2 <- n2 + 1 # Assume we spent the "rest alpha" proportionally (in the planning phase) # therefore we set "mode = 1". cp <- getCP(n2, design$p1, design, k, mode = 1, alpha = 0.05) } n2