var_error_A: Estimate the error variance of the probability-based effect...

In jadahlke/psychmeta: Psychometric Meta-Analysis Toolkit

Estimate the error variance of the probability-based effect size (A, AUC, the common language effect size [CLES])

Description

Estimates the error variance of the probability-based common language effect size (A, AUC, CLES)

Usage

var_error_A(A, n1, n2 = NA)

var_error_auc(A, n1, n2 = NA)

var_error_cles(A, n1, n2 = NA)

Arguments

A	Vector of probability-based effect sizes (common language effect sizes)
n1	Vector of sample sizes from group 1 (or the total sample size with the assumption that groups are of equal size, if no group 2 sample size is supplied).
n2	Vector of sample sizes from group 2.

Details

The sampling variance of a A (also called AUC [area under curve] or CLES [common-language effect size]) value is:

\frac{\left[\left(\frac{1}{n_{1}}\right)+\left(\frac{1}{n_{2}}\right)+\left(\frac{1}{n_{1}n_{2}}\right)\right]}{12}

When groups 1 and 2 are of equal size, this reduces to

\frac{\left[\left(\frac{1}{n}\right)+\left(\frac{1}{n^{2}}\right)\right]}{3}

Value

A vector of sampling-error variances.

References

Ruscio, J. (2008). A probability-based measure of effect size: Robustness to base rates and other factors. *Psychological Methods, 13*(1), 19–30. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1037/1082-989X.13.1.19")}

Examples

var_error_A(A = 1, n1 = 30, n2 = 30)
var_error_auc(A = 1, n1 = 60, n2 = NA)
var_error_cles(A = 1, n1 = 30, n2 = 30)

jadahlke/psychmeta documentation built on Feb. 11, 2024, 9:15 p.m.