sample_size_2arm_binary {frequentistSSDBinary}

Calculate the sample size for each arm in a two-arm trial

Description

Calculate the sample size for each arm in a two-arm trial

Usage

sample_size_2arm_binary(p0, p1, p2, diff = 0, selection.prob = 0.9,
                        alpha = 0.1, beta = 0.2)

Arguments

p0

the successful probability of historical data

p1

the response rate of arm 1

p2

the response rate of arm 2

diff

the equivalence margin

selection.prob

the probability of selection of a superior arm. The default value is selection.prob = 0.9

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

Value

sample_size_2arm_binary() returns required sample size for each arm

Author(s)

Chia-Wei Hsu, Zongheng Cai, Haitao Pan

References

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)

Examples

sample_size_2arm_binary(p0 = 0.2, p1 = 0.415, p2 = 0.615)