optimal_2arm_binary {frequentistSSDBinary} | R Documentation |
Find the optimal parameters used in the get_oc_2arm()
function
optimal_2arm_binary(p0, p1, p2, alpha = 0.1, beta = 0.2, tot_sample)
p0 |
the response rate of historical data |
p1 |
the response rate of arm 1 |
p2 |
the response rate of arm 2 |
alpha |
the type I error to be controlled. The default value is alpha = 0.1 |
beta |
the type II error to be controlled. The default value is beta = 0.2 |
tot_sample |
the required sample size for each arm from function |
optimal_2arm_binary()
returns: (1) alpha: type I error (2) beta: typeII error (3) r1: the maximum number of successes in stage 1 which will terminate trial (4) n1: the number of subjects in stage 1 (5) r2: the maximum number of successes in stage 2 not to warrant further investigation (6) n: the total number of subjects (stage 1 + stage 2) (7) ESS: the expected sample size for each arm (8) PS:the probability of early stopping
Chia-Wei Hsu, Zongheng Cai, Haitao Pan
Cai, Z., Pan, H., Wu, J., Hsu, C.W. (2024). Uncontrolled Randomized Screening Selection Design for Pediatric Oncology Trials. Accepted in Book Chapter of "Master Protocol Clinical Trial for Efficient Evidence Generation"
Wu, J., Pan, H., & Hsu, C. W. (2022). Two-stage screened selection designs for randomized phase II trials with time-to-event endpoints. Biometrical Journal, 64(7), 1207-1218
Yap, C., Pettitt, A. & Billingham, L. Screened selection design for randomised phase II oncology trials: an example in chronic lymphocytic leukaemia. BMC Med Res Methodol 13, 87 (2013)
optimal_2arm_binary(p0 = 0.2, p1 = 0.415, p2 = 0.615, tot_sample = 21)