Nothing
zfleiss <- function(dat, N, design, conf.level){
N. <- 1 - ((1 - conf.level) / 2)
# Sampling for Epidemiologists, Kevin M Sullivan
a <- dat[,1]
n <- dat[,2]
p <- a / n
q <- (1 - p)
# 'n' = the total number of subjects sampled. 'N' equals the size of the total population.
var.fl <- ((p * q) / (n - 1)) * ((N - n) / N)
# Design effect equals [var.obs] / [var.srs].
# var.fl has been computed assuming simple random sampling so if an argument for design effect is provided we need to adjust se.wil accordingly:
se.fl <- sqrt(design * var.fl)
df <- n - 1
t <- abs(qt(p = N., df = df))
low <- p - (t * se.fl)
upp <- p + (t * se.fl)
rval <- data.frame(est = p, se = se.fl, lower = low, upper = upp)
rval
}
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