d_from_means: Obtain Cohen's _d_ from means, standard deviations, and ns
In wviechtb/escalc: Package for Computing Effect Sizes

Description Usage Arguments Details Value References Examples

View source: R/d_from_means.R

This function converts means, standard deviations, and sample sizes to Cohen's d.

1	d_from_means(m1, m2, sd1, sd2, n1, n2, bias_correct = FALSE)

`m1, m2`	A numerical vector with the means of the two groups formed by the dichotomous variable.
`sd1, sd2`	A numerical vector with the standard deviations of the two groups formed by the dichotomous variable. Note that the nth element of these vectors must correspond to the nth elements of the `m1`, `m2` vectors.
`n1, n2`	A numerical vector with the sample sizes of the two groups formed by the dichotomous variable. Note that the nth element of these vectors must correspond to the nth elements of the `m1`, `m2` vectors.
`bias_correct`	Logical to indicate if the d-values should be bias-corrected. Can also be a vector.

The formula that is used is the following (see e.g. Lakens, 2013):

d= \frac{\bar{X}_1 - \bar{X}_1} {√{\frac{(n_1 - 1)SD_1^2 + (n_2 - 1)SD_2^2}{n_1 + n_2 - 2}}}

A data frame with in the first column, Cohen's d values, and in the second column, the corresponding variances.

Lakens, D. (2013) Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4, p. 863. doi: 10.3389/fpsyg.2013.00863

escalc::d_from_means(m1 = 2.828427,
                     m2 = 2.123041,
                     sd1 = 0.230101,
                     sd2 = 0.259281,
                     n1 = 126,
                     n2 = 89);