R/beta2g.R

In copariuc/CorMat2ES: Converts a correlation matrix in an effect size object

if (!require(esc)) install.packages("esc")
library(esc)

#' Conversion from a Beta coefficient to an effect size object
#' @description
#' This function converts form a beta coefficient to an effect size object
#'
beta2es <-function(Study, Type, Beta, SDy, N1, N2, Y, X, Ryy, Rxx){
  rec <- 1; es <- data.frame(study = NA, es = NA, weight = NA, sample.size = NA, se = NA, var = NA,
                             ci.lo = NA, ci.hi = NA, measure = NA, X = NA, Rxx = NA, Y = NA, Ryy = NA)
  while(rec <= length(Beta)){
    g <- esc::esc_beta(beta = Beta[rec], sdy = SDy[rec], grp1n = N1, grp2n = N2, es.type = Type, study = Study)
    # Binding all data
    es <- rbind(es, c(Study, g$es, g$w, g$totaln, g$se, g$var, g$ci.lo, g$ci.hi, g$measure,
                      X[rec], Rxx[rec], Y[rec], Ryy[rec]))
    rec <- rec + 1
  }
  colnames(es) <- c("study", "es", "weight", "sample.size", "se", "var", "ci.lo", "ci.hi", "measure",
                        "X", "Rxx", "Y", "Ryy");  return(es[-1,])
}

# beta <- c(1.00, .01, .01)
# sd <- c(0.06 * sqrt(160), 0.05 * sqrt(160), 0.05 * sqrt(160))
# Y <- c(rep("Harmfull", 3)); X <- c("Psychopathy", "Machiavellianism", "Narcissism")
# Ryy <- c(rep(NA, 3)); Rxx <- c(rep(.72, 3))
#
# temp <- beta2es(Study = "dem$author", Type = "g", Beta = beta, SDy = sd,
#                 N1 = 87, N2 = 87, Y = Y, X = X, Ryy = Ryy, Rxx = Rxx)