Sample size for a two-arm binary / responder endpoint

Comparison of two proportions (e.g. responder rates), via the normal approximation with unequal allocation; matches stats::power.prop.test in the balanced case.

Usage

sampleSizeBinary(
  p1,
  p2,
  power = 0.8,
  sig_level = 0.05,
  ratio = 1,
  sides = 2L,
  dropout = 0,
  cluster_size = NULL,
  icc = NULL
)

Arguments

p1

Control-arm proportion.

p2

Treatment-arm proportion.

power, sig_level, ratio, sides, dropout, cluster_size, icc

As in sampleSizeContinuous().

Value

A trial_power object.

See also

sampleSizeContinuous(), powerBinary()

Examples

sampleSizeBinary(p1 = 0.30, p2 = 0.50)      # responder-rate 30% vs 50%
#> <trial_power> two-proportion
#>   effect: p1=0.3, p2=0.5
#>   power 0.80 | alpha 0.05 (2-sided) | allocation 1:1
#>   n per arm: control 93, treatment 93  (total 186)