R/paired-t.R

In compute.es: Compute Effect Sizes

# PAIRED T-TEST TO d

# tes2 <- function(t, n, r, level = 95) {
#   d <- t * sqrt(2 * (1 - r) / n)
#   var.d <- 1 / n + d^2 / (2 * n)
#   alpha <- (100 - level) / 100
#   crit <- qt(alpha / 2, n - 1, lower.tail = FALSE)
#   l.d <- d - crit * sqrt(var.d)
#   u.d <- d + crit * sqrt(var.d)
#   out <- data.frame(d, var.d, l.d, u.d)
#   out
# }

# tes2(t=-1.9503, n=22, r=.5)
#
#
# # THIS PROCEDURE IS MOST PRECISE AS IT IS BASED ON EXACT 95% Ci VS.
# # THE FUNCTION I CREATED ABOVE IS AN APPROXIMATION UNDER A NORMAL DISTRIBUTION
# # library(MBESS)
# # ci.sm(ncp = -1.9503, N = 22, conf.level = .95)