# correct_r_coarseness: Correct correlations for scale coarseness In psychmeta: Psychometric Meta-Analysis Toolkit

## Description

Corrects correlations for scale coarseness.

## Usage

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 correct_r_coarseness( r, kx = NULL, ky = NULL, n = NULL, dist_x = "norm", dist_y = "norm", bin_value_x = c("median", "mean", "index"), bin_value_y = c("median", "mean", "index"), width_x = 3, width_y = 3, lbound_x = NULL, ubound_x = NULL, lbound_y = NULL, ubound_y = NULL, index_values_x = NULL, index_values_y = NULL ) 

## Arguments

 r Observed correlation. kx, ky Number of scale points used to measure the x and y variables. Set to NULL to treat as continuously measured. n Optional sample size. dist_x, dist_y Assumed latent distribution of the x and y variables. bin_value_x, bin_value_y Are the scale points used to measure the of the x and y variables assumed to represent bin medians, means, or index values? width_x, width_y For symmetrically distributed variables, how many standard deviations above/below the latent mean should be be used for the latent variable range to make the correction? (Note: Setting width > 3 produces erratic results.) The latent variable range can alternatively be set using lbound and ubound. lbound_x, lbound_y What lower bound of the range for the latent x and y variables should be used to make the correction? (Note: For normally distributed variables, setting lbound < -3 produces erratic results.) ubound_x, ubound_y What upper bound of the range for the latent x and y variables should be used to make the correction? (Note: For normally distributed variables, setting ubound > 3 produces erratic results.) index_values_x, index_values_y Optional. If bin_value = "index", the bin index values. If unspecified, values 1:k are used.

## Value

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

## References

Aguinis, H., Pierce, C. A., & Culpepper, S. A. (2009). Scale coarseness as a methodological artifact: Correcting correlation coefficients attenuated from using coarse scales. Organizational Research Methods, 12(4), 623–652. doi: 10.1177/1094428108318065

Schmidt, F. L., & Hunter, J. E. (2015). Methods of meta-analysis: Correcting error and bias in research findings (3rd ed.). Sage. doi: 10.4135/9781483398105. pp. 287-288.

Peters, C. C., & Van Voorhis, W. R. (1940). Statistical procedures and their mathematical bases. New York, NY: Mcgraw-Hill. doi: 10.1037/13596-000. pp. 393–399.

## Examples

 1 2 3 correct_r_coarseness(r = .35, kx = 5, ky = 4, n = 100) correct_r_coarseness(r = .35, kx = 5, n = 100) correct_r_coarseness(r = .35, kx = 5, ky = 4, n = 100, dist_x="unif", dist_y="norm") 

psychmeta documentation built on June 1, 2021, 9:13 a.m.