es_from_cohen_d_adj {metaConvert} | R Documentation |
Convert an adjusted Cohen's d value to several effect size measures
Description
Convert an adjusted Cohen's d value to several effect size measures
Usage
es_from_cohen_d_adj(
cohen_d_adj,
n_cov_ancova,
cov_outcome_r,
n_exp,
n_nexp,
smd_to_cor = "viechtbauer",
reverse_d
)
Arguments
cohen_d_adj |
Adjusted Cohen's d (i.e., standardized mean difference) value. |
n_cov_ancova |
number of covariates |
cov_outcome_r |
covariate-outcome correlation (in case of multiple covariates, the multiple correlation) |
n_exp |
number of participants in the experimental/exposed group. |
n_nexp |
number of participants in the non-experimental/non-exposed group. |
smd_to_cor |
formula used to convert the |
reverse_d |
a logical value indicating whether the direction of generated effect sizes should be flipped. |
Details
This function estimates the standard error of an adjusted Cohen's d value and Hedges' g (G), and converts an odds ratio (OR) and correlation coefficients (R/Z).
To estimate the standard error of Cohen's d, the following formula is used (table 12.3 in Cooper):
To estimate other effect size measures, calculations of the
es_from_cohen_d()
function are used (with the exception of the degree of freedom
that is estimated as df = n_exp + n_nexp - 2 - n_cov_ancova
).
Value
This function estimates and converts between several effect size measures.
natural effect size measure | D + G |
converted effect size measure | OR + R + Z |
required input data | See 'Section 1. Cohen's d or Hedges' g' |
https://metaconvert.org/html/input.html | |
References
Cooper, H., Hedges, L.V., & Valentine, J.C. (Eds.). (2019). The handbook of research synthesis and meta-analysis. Russell Sage Foundation.
Examples
es_from_cohen_d_adj(cohen_d_adj = 1, n_cov_ancova = 4, cov_outcome_r = .30, n_exp = 20, n_nexp = 20)