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#' @title Convert effect size d into correlation
#' @name convert_d2r
#'
#' @description Compute effect size correlation from effect size \code{d}.
#'
#' @inheritParams esc_beta
#' @inheritParams convert_d2or
#' @inheritParams esc_mean_sd
#'
#' @return The effect size \code{es}, the standard error \code{se}, the variance
#' of the effect size \code{var}, the lower and upper confidence limits
#' \code{ci.lo} and \code{ci.hi}, the weight factor \code{w} and the
#' total sample size \code{totaln}. Furthermore, Fisher's z and
#' confidence intervals are returned.
#'
#' @references Lipsey MW, Wilson DB. 2001. Practical meta-analysis. Thousand Oaks, Calif: Sage Publications
#' \cr \cr
#' Wilson DB. 2016. Formulas Used by the "Practical Meta-Analysis Effect Size Calculator". Unpublished manuscript: George Mason University
#'
#' @examples
#' convert_d2r(d = 0.7, se = 0.5, grp1n = 70, grp2n = 80)
#'
#' @export
convert_d2r <- function(d, se, v, grp1n, grp2n, info = NULL, study = NULL) {
# check if parameter are complete
if ((missing(se) || is.null(se) || is.na(se)) && (missing(v) || is.null(v) || is.na(v))) {
warning("Either `se` or `v` must be specified.", call. = F)
return(esc_generic(es = NA, v = NA, es.type = NA, grp1n = NA, grp2n = NA, info = NA, study = NA))
}
# do we have se?
if (!missing(se) && !is.null(se) && !is.na(se)) v <- se^2
# do we have a separate info string?
if (is.null(info)) info <- "effect size d to effect size correlation"
p <- grp1n / (grp1n + grp2n)
es <- d / sqrt(d^2 + 1 / (p * (1 - p)))
v <- v / (v + 1 / (p * (1 - p)))
# compute fisher's corrections for r
es.zr <- convert_r2z(es)
# return effect size d
structure(
class = c("esc", "convert_d2r"),
list(
es = es,
se = sqrt(v),
var = v,
ci.lo = convert_z2r(lower_d(es.zr, v)),
ci.hi = convert_z2r(upper_d(es.zr, v)),
w = 1 / v,
zr = es.zr,
ci.lo.zr = lower_d(es.zr, v),
ci.hi.zr = upper_d(es.zr, v),
totaln = (grp1n + grp2n),
measure = "r",
info = info,
study = study
)
)
}
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