This function calculates the P(reject alternative hypothesis)

fleming2st_reject_Ha(n1, n2, r1, a, r2, p0, pa)

Arguments

n1

total number of patients in stage1

n2

total number of patients in stage2

r1

critical value futility for the first stage

a

critical value efficacy for the first stage

r2

critical value futility/efficacy for the second stage

p0

true success probability under H0

pa

true success probability under Ha

Details

if x1<=r1 --> stop futility
if x1>=a --> stop efficacy
if (x1+x2)<=r2 --> futility
with x1 the number of successes in the first stage and x2 the number of successes in the second stage

References

Mander AP, Thompson SG. Two-stage designs optimal under the alternative hypothesis for phase II cancer clinical trials. Contemporary Clinical Trials 2010;31:572–578 Qin F et al. Optimal, minimax and admissible two-stage design for phase II oncology clinical trials. BMC Medical Research Methodology 2020;20:126

Examples

fleming2st_reject_Ha(n1=13, n2=7, r1=0, a=3, r2=2, p0=0.05, pa=0.25)
#> $N
#> [1] 20
#> 
#> $n1
#> [1] 13
#> 
#> $r1
#> [1] 0
#> 
#> $a
#> [1] 3
#> 
#> $n2
#> [1] 7
#> 
#> $r2
#> [1] 2
#> 
#> $alpha_temp
#> [1] 0.07355503
#> 
#> $beta_temp
#> [1] 0.0970475
#> 
#> $EN.p0
#> [1] 16.23505
#> 
#> $EN.pa
#> [1] 15.16191
#> 
#> $PET.p0
#> [1] 0.5378499
#> 
#> $PET.pa
#> [1] 0.6911556
#>