# adjust_n_d: Adjusted sample size for a non-Cohen _d_ value for use in a... In psychmeta: Psychometric Meta-Analysis Toolkit

## Description

This function is used to convert a non-Cohen \mjseqnd value (e.g., Glass' \mjeqn\Delta\Delta) to a Cohen's \mjseqnd value by identifying the sample size of a Cohen's \mjseqnd that has the same standard error as the non-Cohen \mjseqnd. This function permits users to account for the influence of sporadic corrections on the sampling variance of \mjseqnd prior to use in a meta-analysis.

## Usage

 1 adjust_n_d(d, var_e, p = NA) 

## Arguments

 d Vector of non-Cohen \mjseqnd standardized mean differences. var_e Vector of error variances of standardized mean differences. p Proportion of participants in a study belonging to one of the two groups being contrasted.

## Details

The adjusted sample size is computed as: \mjdeqnn_adjusted=\fracd^2p(1-p)+22p(1-p)var_en_adjusted = ((d^2 * p * (1 - p) + 2) / (2 * p * (1 - p) * 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. Chapter 7 (Equations 7.23 and 7.23a).

## Examples

 1 adjust_n_d(d = 1, var_e = .03, p = NA) 

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