Exact sequential confidence intervals for vaccine or prevention efficacy

Forms a sequential confidence interval after each completed analysis by intersecting the exact repeated confidence intervals through that analysis.

Usage

sequentialCIBinomialExact(
  gsD,
  n.I = NULL,
  x = NULL,
  conf.level = 0.95,
  tol = 1e-08,
  maxiter = 100
)

Arguments

gsD

A gsSurv object with non-binding test.type 1, 4, 6, or 8.

n.I

Increasing integer total event counts at completed analyses. If NULL, planned integer event counts from toInteger(gsD) are used.

x

Integer experimental-arm event counts at the analyses in n.I.

conf.level

Two-sided confidence level.

tol

Absolute tolerance for bisection on the conditional binomial event-probability scale.

maxiter

Maximum bisection iterations for each confidence limit.

Value

A data frame with one row per completed analysis containing the observed counts, efficacy estimate, sequential confidence limits, confidence level, and one-sided tail level.

Details

The interval is the inversion of sequentialPValueBinomialExact applied in both directions: a candidate efficacy remains in the confidence set only when neither one-sided repeated test has rejected it at any completed analysis. Thus the sequential interval through analysis j is the intersection of repeated intervals 1 through j.

See also

ciBinomialExact, repeatedCIBinomialExact, sequentialPValueBinomialExact

Examples

design <- gsSurv(
  k = 3, test.type = 4, timing = c(.45, .7), ratio = 3,
  hr = .3, hr0 = .7
)
counts <- toBinomialExact(design)$n.I
# \donttest{
sequentialCIBinomialExact(design, counts, x = c(12, 23, 38))
#>   Analysis n.I  x  estimate  conf.low conf.high conf.level tail_alpha
#> 1        1  31 12 0.7894737 0.3792904 0.9345737       0.95      0.025
#> 2        2  48 23 0.6933333 0.3792904 0.8562642       0.95      0.025
#> 3        3  68 38 0.5777778 0.3792904 0.7471530       0.95      0.025
# }