#F2R, t2R, r.CI
# made by joe hilgard in early 2014 *flexes biceps*
Cramer = function(chisq, n, k=2) {
v = sqrt(chisq/(n*(k-1)))
return(v)
}
# Standard error according to
# http://stats.stackexchange.com/questions/8487/how-do-you-calculate-confidence-intervals-for-cohens-d
stderr.d = function(d, n1, n2) {
term1 = (n1+n2)/(n1*n2) + d^2 / (2*(n1+n2-2))
term2 = (n1+n2)/(n1+n2-2)
return(sqrt(term1*term2))
}
# Odds Ratio into Cohen's d
# Hasselblad & Hedges (1995) technique
OR.to.d = function(OR=NULL, b=NULL) {
if (!is.null(OR)) b1 = log(OR)
if (!is.null(b) & !is.null(OR)) if (b1 != b) print("Nonmatching OR and b! One or the other, please.")
if (is.null(b)) b = b1
return(b * sqrt(3)/pi)
}
d2r = function(d, n1, n2, width=.95) {
r = d / sqrt(d ^ 2 + 4)
term1 = (n1+n2)/(n1*n2) + d^2/(2*(n1+n2-2))
term2 = (n1+n2)/(n1+n2-2)
StdErr.d = sqrt(term1*term2)
a = ((n1+n2)^2)/(n1*n2)
StdErr.r = sqrt(a^2 * StdErr.d ^ 2 / ((d ^ 2 + a) ^ 3))
return(list("r"=r, "StdErr.r"=StdErr.r))
}
d2r2z = function(d, n1, n2) {
r = d2r(d, n1, n2)[[1]]
StdErr.r = d2r(d, n1, n2)[[2]]
FisherZ = 0.5 * log((1 + r) / (1 - r))
StdErr.z = StdErr.r / (1 - r ^ 2)
return(list("Z" = FisherZ, "StdErr.z" = StdErr.z))
}
d2t = function(d, n1, n2) {
t = d * sqrt(n1 + n2 - 2) / 2
return(t)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.