CLAST (version 1.0.1)

inference: Exact limits from outcome

Description

Calculates exact upper and lower confidence limits from the outcome of a multi-stage group sequential trial.

Usage

inference(n, a, b, y, alpha, type)

Arguments

n

Design vector of planned sample sizes

a

Design vector of lower futility boundaries

b

Design vector of upper superiority boundaries

y

Actual outcome of experiment

alpha

exact coverage error

type

character, either "LR", "CP", "JT" or "ML"

Value

list with components

lower

exact lower limit, type dependent

upper

exact lower limit, type dependent

est

ML estimate

type

selected ordering function "LR", "CP", "JT" or "ML"

References

Lloyd, C.J. (2020) Exact confidence limits after a group sequential single arm binary trial. Statistics in Medicine, Volume 38, 2389-2399.

Examples

# NOT RUN {
# Example from table 1 of Lloyd (2020)
  n=c(5,6,5,9)
  a=c(2,4,5,12)
  b=c(5,9,11,13)
  y=c(4,2,5) # This is the actual outcome. The trial stopped for
#              superiority at stage m=3 with s=11 successes.
  inference(n,a,b,y,type="CP")
# Results happen to be identical for type="LR" but different
# for the alternative ordering functions "JT" and "ML"
# }