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Correct correlations for artificial dichotomization of one or both variables

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

Vector of correlations attenuated by artificial dichomization.

Vector of proportions of the distribution on either side of the split applied to X (set as NA if X is continuous).

Vector of proportions of the distribution on either side of the split applied to Y (set as NA if Y is continuous).

Optional vector of sample sizes.

Additional arguments.

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

n

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

Schmidt, F. L., & Hunter, J. E. (2015). Methods of meta-analysis: Correcting error and bias in research findings (3rd ed.). Thousand Oaks, CA: SAGE. https://doi.org/10/b6mg. pp. 43<U+2013>44.

# NOT RUN { correct_r_dich(r = 0.32, px = .5, py = .5, n = 100) # }

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