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2024 Jan 18
0
Is there any design based two proportions z test?
...he elementary result that the variance of the difference of two independent random variables is the sum of their variances, plus the observation that the width of the confidence interval is 2*z*SE, where z is the normal quantile corresponding to the confidence level (e.g., 1.96 for a 95% CI). ciDiff <- function(ci1, ci2, level=0.95){ p1 <- mean(ci1) p2 <- mean(ci2) z <- qnorm((1 - level)/2, lower.tail=FALSE) se1 <- (ci1[2] - ci1[1])/(2*z) se2 <- (ci2[2] - ci2[1])/(2*z) seDiff <- sqrt(se1^2 + se2^2) (p1 - p2) + c(-z, z)*seDiff } > > Example: Pr...