correct_r_dich: Correct correlations for artificial dichotomization of one or...

In psychmeta: Psychometric Meta-Analysis Toolkit

Correct correlations for artificial dichotomization of one or both variables

Description

Correct correlations for artificial dichotomization of one or both variables.

Usage

correct_r_dich(r, px = NA, py = NA, n = NULL, ...)

Arguments

r	Vector of correlations attenuated by artificial dichotomization.
px	Vector of proportions of the distribution on either side of the split applied to X (set as NA if X is continuous).
py	Vector of proportions of the distribution on either side of the split applied to Y (set as NA if Y is continuous).
n	Optional vector of sample sizes.
...	Additional arguments.

Details

r_{c}=\frac{r_{obs}}{\left[\frac{\phi\left(p_{X}\right)}{p_{X}\left(1-p_{X}\right)}\right]\left[\frac{\phi\left(p_{Y}\right)}{p_{Y}\left(1-p_{Y}\right)}\right]}

Value

Vector of correlations corrected for artificial dichotomization (if n is supplied, corrected error variance and adjusted sample size is also reported).

References

Schmidt, F. L., & Hunter, J. E. (2015). Methods of meta-analysis: Correcting error and bias in research findings (3rd ed.). Sage. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.4135/9781483398105")}. pp. 43–44.

Examples

correct_r_dich(r = 0.32, px = .5, py = .5, n = 100)

psychmeta documentation built on June 22, 2024, 6:52 p.m.