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Conversion from Means and Standard Deviations to Cohen's d

Source: R/utils.R
means.to.d.Rd

Helper function to convert means and standard deviations to Cohen's d.

Usage

means.to.d(
  mu1,
  mu2 = 0,
  sd1 = 1,
  sd2 = 1,
  n.ratio = 1,
  n2,
  paired = FALSE,
  rho.paired = 0.5,
  verbose = 1
)

Arguments

mu1

mean of the first group.

mu2

mean of the second group.

sd1

standard deviation of the first group.

sd2

standard deviation of the second group.

n.ratio

n1 / n2 ratio (applies to independent samples only).

n2

integer; sample size in the second group (or for the single group in paired samples).

paired

if TRUE paired samples

rho.paired

correlation between repeated measures for paired samples (e.g., pretest and post-test).

verbose

1 by default (returns test, hypotheses, and results), if 2 a more detailed output is given (plus key parameters and definitions), if 0 no output is printed on the console.

Value

parms

list of parameters used in calculation.

d

Cohen's d

pooled.sd

Pooled standard deviation

var.ratio

Ratio of the variance in the two groups (applies to independent samples only)

n1

Sample size group 1 (applies to independent samples only)

n2

Sample size group 2

Examples



# means and standard deviations from independent samples
means.to.d(mu1 = 20, mu2 = 17.5,
           sd1 = 5, sd2 = 15,
           n2 = 30, n.ratio = 1)
#> Warning: Interpretation of Cohen's d may no longer be valid when variances differ beyond sampling error.
#>         d 
#> 0.2236068 

# means and standard deviations from paired samples
means.to.d(mu1 = 20, mu2 = 17.5,
           sd1 = 5, sd2 = 15,
           n2 = 30, n.ratio = 1,
           paired = TRUE,
           rho.paired = 0.50)
#> Warning: Interpretation of Cohen's d may no longer be valid when variances differ beyond sampling error.
#>         d 
#> 0.1889822