Exact confidence intervals for vaccine or prevention efficacy

Computes a fixed-look Clopper–Pearson confidence interval for vaccine or prevention efficacy after conditioning on the total number of events.

Usage

ciBinomialExact(
  x,
  n,
  ratio = 1,
  conf.level = 0.95,
  alternative = c("two.sided", "lower", "upper")
)

Arguments

x: Number of events in the experimental group.
n: Total number of events.
ratio: Experimental-to-control randomization ratio.
conf.level: Confidence level.
alternative: Character string specifying a two-sided interval, a lower confidence bound, or an upper confidence bound for efficacy.

Value

A one-row data frame containing the observed counts, randomization ratio, efficacy estimate, confidence limits, and confidence level.

Details

Conditional on n, x is binomial with event probability p in the experimental group. Clopper–Pearson limits for p are transformed using efficacy = 1 - p / (ratio * (1 - p)). Because this transformation is decreasing, the probability limits are reversed on the efficacy scale. The same calculation applies to vaccine efficacy (VE) and prevention efficacy (PE).

Examples

ciBinomialExact(x = 16, n = 78, ratio = 3)
#>    x  n ratio  estimate  conf.low conf.high conf.level          method
#> 1 16 78     3 0.9139785 0.8490973 0.9536666       0.95 Clopper-Pearson