es_from_md_pval {metaConvert} | R Documentation |
Convert a mean difference between two independent groups and its p-value into several effect size measures
Description
Convert a mean difference between two independent groups and its p-value into several effect size measures
Usage
es_from_md_pval(
md,
md_pval,
n_exp,
n_nexp,
smd_to_cor = "viechtbauer",
reverse_md
)
Arguments
md |
mean difference between two independent groups |
md_pval |
p-value of the mean difference |
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_md |
a logical value indicating whether the direction of generated effect sizes should be flipped. |
Details
This function converts the p-value of a mean difference into a standard error (Cochrane Handbook section 6.5.2.3):
t = qt(\frac{md\_pval}{2}, df = n\_exp + n\_nexp - 2)
md\_se = |\frac{md}{t}|
Calculations of the es_from_md_se
function are then used to estimate the Cohen's d and other effect size measures.
Value
This function estimates and converts between several effect size measures.
natural effect size measure | MD + D + G |
converted effect size measure | OR + R + Z |
required input data | See 'Section 10. Mean difference and dispersion (crude)' |
https://metaconvert.org/html/input.html | |
References
Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, Welch VA (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.3 (updated February 2022). Cochrane, 2022. Available from www.training.cochrane.org/handbook.
Examples
es_from_md_pval(md = 4, md_pval = 0.024, n_exp = 20, n_nexp = 22)