psychmeta (version 2.6.5)

correct_r_dich: 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, ...)

Value

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

Arguments

r

Vector of correlations attenuated by artificial dichomization.

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

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

References

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

Examples

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