adjust_n_d: Adjusted sample size for a non-Cohen _d_ value for use in a...

Description Usage Arguments Details Value References Examples

View source: R/adjust_n.R

Description

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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)

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