View source: R/es_from_stand_MD.R
es_from_md_ci | R Documentation |
Convert a mean difference between two independent groups and 95% CI into several effect size measures
es_from_md_ci(
md,
md_ci_lo,
md_ci_up,
n_exp,
n_nexp,
smd_to_cor = "viechtbauer",
max_asymmetry = 10,
reverse_md
)
md |
mean difference between two independent groups |
md_ci_lo |
lower bound of the 95% CI of the mean difference |
md_ci_up |
upper bound of the 95% CI 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 |
max_asymmetry |
A percentage indicating the tolerance before detecting asymmetry in the 95% CI bounds. |
reverse_md |
a logical value indicating whether the direction of generated effect sizes should be flipped. |
This function converts 95% CI of a mean difference into a standard error (Cochrane Handbook section 6.5.2.3):
md\_se = \frac{md\_ci\_up - md\_ci\_lo}{2 * qt(0.975, df = n\_exp + n\_nexp - 2)}
Calculations of the es_from_md_se()
function are
then used to estimate the Cohen's d and other effect size measures.
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/input.html | |
Higgins JPT, Li T, Deeks JJ (editors). Chapter 6: Choosing effect size measures and computing estimates of effect. In: 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.
es_from_md_ci(md = 4, md_ci_lo = 2, md_ci_up = 6, n_exp = 20, n_nexp = 22)
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