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.
Vector of correlations.
Vector of error variances.
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
A vector of adjusted sample sizes.
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.
adjust_n_r(r = .3, var_e = .01)
----------------------------------------------------- psychmeta version 2.3.3 -- Please report any bugs to github.com/psychmeta/psychmeta/issues or email@example.com 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 Attaching package: 'psychmeta' The following object is masked from 'package:stats': filter  83.81
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