Find stopping boundary via binomial or beta-binomial distribution. For the latter, the overdispersion factor (or design effect) by which the variance exceeds the regular binomial variance is printed.

Find stopping boundary via binomial or beta-binomial distribution. For the latter, the overdispersion factor (or design effect) by which the variance exceeds the regular binomial variance is printed.

Usage

findbound(
  n,
  alpha_test = 0.025,
  pH0 = 0.5,
  alternative = "greater",
  icc = NULL
)

Arguments

n

total number of events

alpha_test

nominal alpha for the binomial test

pH0

proportion of events in the experimental arm under the null hypothesis, typically based on randomization ratio (e.g. 0.5 for a 1:1 randomization)

alternative

direction of alternative, "less" or "greater"

icc

intraclass correlation if there is more than one event per patient

Value

number of events in the experimental group that would lead to a stopping

Examples

findbound(n=20, alpha_test=0.025, pH0 = 0.5, alternative="greater")
#> [1] 15
findbound(n=20, alpha_test=0.025, pH0 = 0.5, alternative="less")
#> [1] 5