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#' @title The Katz log confidence interval for the ratio of probabilities
#' @description The Katz log confidence interval for the ratio of probabilities
#' @description Described in Chapter 4 "The 2x2 Table"
#' @param n the observed counts (a 2x2 matrix)
#' @param alpha the nominal level, e.g. 0.05 for 95% CIs
#' @examples
#' Katz_log_CI_2x2(perondi_2004)
#' Katz_log_CI_2x2(ritland_2007)
#' @export
#' @return An object of the [contingencytables_result] class,
#' basically a subclass of [base::list()]. Use the [utils::str()] function
#' to see the specific elements returned.
Katz_log_CI_2x2 <- function(n, alpha = 0.05) {
validateArguments(mget(ls()))
n1p <- n[1, 1] + n[1, 2]
n2p <- n[2, 1] + n[2, 2]
# Estimates of the two probabilities of success
pi1hat <- n[1, 1] / n1p
pi2hat <- n[2, 1] / n2p
# Estimate of the ratio of probabilities (phihat)
estimate <- pi1hat / pi2hat
# Standard error of log(estimate)
SE <- sqrt(1 / n[1, 1] + 1 / n[2, 1] - 1 / n1p - 1 / n2p)
# The upper alpha / 2 percentile of the standard normal distribution
z <- qnorm(1 - alpha / 2, 0, 1)
# Calculate the confidence limits
L <- exp(log(estimate) - z * SE)
U <- exp(log(estimate) + z * SE)
# Uncomputable limits -> uninformative interval
if (n[1, 1] == 0 || n[2, 1] == 0) {
L <- 0
U <- Inf
}
return(
contingencytables_result(
list("lower" = L, "upper" = U, "estimate" = estimate),
sprintf(
"The Katz log CI: estimate = %6.4f (%g%% CI %6.4f to %6.4f)",
estimate, 100 * (1 - alpha), L, U
)
)
)
}
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