escompute: escompute

View source: R/escompute.R

escomputeR Documentation

escompute

Description

Function that computes Hedges' g and its sampling variance for an one-sample mean and a two-independent means, Fisher's r-to-z transformed correlation coefficient and its sampling variance for a raw correlation coefficient and computes a p-value as in the primary studies was done.

Usage

escompute(
  mi,
  ri,
  ni,
  sdi,
  m1i,
  m2i,
  n1i,
  n2i,
  sd1i,
  sd2i,
  tobs,
  yi,
  vi,
  alpha,
  side,
  measure
)

Arguments

mi

A vector of group means for one-sample mean

ri

A vector of raw correlation coefficients

ni

A vector of sample sizes for one-sample mean

sdi

A vector of standard deviations for one-sample mean

m1i

A vector of means in group 1 for two-independent means

m2i

A vector of means in group 2 for two-independent means

n1i

A vector of sample sizes in group 1 for two-independent means

n2i

A vector of sample sizes in group 2 for two-independent means

sd1i

A vector of standard deviations in group 1 for two-independent means

sd2i

A vector of standard deviations in group 2 for two-independent means

tobs

A vector of t-values

yi

A vector of standardized effect sizes

vi

A vector of sampling variances belonging to the standardized effect sizes (yi)

alpha

A numerical value specifying the alpha level as used in primary studies

side

A character indicating the direction of the tested hypothesis in the primary studies (either "right" or "left")

measure

A character indicating what kind of effect size should be computed (Hedges' g or Fisher's r-to-z transformed correlation coefficients) and which arguments are used as input ("M", "MT", "MD", "MDT", or "COR"). See Details below.

Details

The measure argument has to be used to specify the desired effect size and what input parameters are used. There are six options:

  • "M" for one-sample mean with mi, ni, sdi, alpha, and side as input parameters

  • "MT" for one-sample mean with tobs, ni, alpha, and side as input parameters

  • "MD" for two-sample mean with m1i, m2i, n1i, n2i, sd1i, sd2i, alpha, and side as input parameters

  • "MDT" for two-sample mean with tobs, n1i, n2i, alpha, and side as input parameters

  • "COR" for raw correlation coefficients with ri, ni, alpha, and side as input parameters

  • "SPE" for user-specified standardized effect sizes and sampling variances with yi, vi, alpha, and side as input parameters

Value

Function returns a data frame with standardized effect sizes (yi), variances of these standardized effect sizes (vi), z-values (zval), p-values as computed in primary studies (pval), and critical z-values (zcv).

Author(s)

Robbie C.M. van Aert R.C.M.vanAert@tilburguniversity.edu


RobbievanAert/puniform documentation built on Sept. 22, 2023, 2:53 a.m.