es_from_md_ci {metaConvert}

Convert a mean difference between two independent groups and 95% CI into several effect size measures

Description

Convert a mean difference between two independent groups and 95% CI into several effect size measures

Usage

es_from_md_ci(
  md,
  md_ci_lo,
  md_ci_up,
  n_exp,
  n_nexp,
  smd_to_cor = "viechtbauer",
  reverse_md
)

Arguments

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 cohen_d value into a coefficient correlation (see details).

reverse_md

a logical value indicating whether the direction of generated effect sizes should be flipped.

Details

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.

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, 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.

Examples

es_from_md_ci(md = 4, md_ci_lo = 2, md_ci_up = 6, n_exp = 20, n_nexp = 22)