d_from_r_pb: Obtain Cohen's _d_ from the point biserial correlation _r_

In wviechtb/transformer: Package for Computing Effect Sizes

Description

This function converts the point biserial correlation r to Cohen's d.

Usage

d_from_r_pb(
  r_pb,
  n1,
  n2,
  baseRateSensitive = FALSE,
  biasCorrect = FALSE,
  crosssectionalSampling = FALSE
)

Arguments

r_pb	A numerical vector with one or more point biserial r values.
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 element of the r_pbs vector.
baseRateSensitive	Whether to compute tyhe base rate sensitive Cohen's d or not (see McGrath & Meyer, 2006).
biasCorrect	Logical to indicate if the d-values should be bias-corrected. Can also be a vector.
crosssectionalSampling	Logical ...

Details

The formula that is used is the following (see e.g. Borenstein et al., 2009):

d= \frac{2 r_{pbs}}{√{1 - r^2}}

Value

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

References

Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009) Introduction to Meta-Analysis, Chichester, UK: John Wiley & Sons, Ltd.

Also see:

McGrath, R. E. & Meyer, G. J. (2006) When Effect Sizes Disagree: The Case of r and d. Psychological Methods, 11, 386-401, doi:doi: 10.1037/1082-989X.11.4.386386

Examples

escalc::d_from_r_pb(r_pb = .3,
                    n1 = 50, n2 =50)

wviechtb/transformer documentation built on Jan. 10, 2020, 11:56 a.m.