adjust_n_r: Adjusted sample size for a non-Pearson correlation...

Description Usage Arguments Details Value References Examples

View source: R/adjust_n.R

Description

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This function is used to compute the adjusted sample size of a non-Pearson correlation (e.g., a tetrachoric correlation) based on the correlation and its estimated error variance. This function allows users to adjust the sample size of a correlation corrected for sporadic artifacts (e.g., unequal splits of dichotomous variables, artificial dichotomization of continuous variables) prior to use in a meta-analysis.

Usage

1
adjust_n_r(r, var_e)

Arguments

r

Vector of correlations.

var_e

Vector of error variances.

Details

The adjusted sample size is computed as:

\mjdeqn

n_adjusted=\frac(r^2-1)^2+var_evar_en_adjusted = ((r^2 - 1)^2 + var_e) / var_e

Value

A vector of adjusted sample sizes.

References

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. Equation 3.7.

Examples

1
adjust_n_r(r = .3, var_e = .01)

Example output

-----------------------------------------------------  psychmeta version 2.3.3  --

Please report any bugs to github.com/psychmeta/psychmeta/issues
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We work hard to produce these open-source tools for the R community, 
please cite psychmeta when you use it in your research: 
  Dahlke, J. A., & Wiernik, B. M. (2018). psychmeta: An R package for 
     psychometric meta-analysis. Applied Psychological Measurement. 
     Advance online publication. https://doi.org/10.1177/0146621618795933

Find info about psychmeta on the web at psychmeta.com and twitter.com/psychmetaR

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