es_from_means_ci {metaConvert}

Convert means and 95% CI of two independent groups several effect size measures

Description

Convert means and 95% CI of two independent groups several effect size measures

Usage

es_from_means_ci(
  mean_exp,
  mean_ci_lo_exp,
  mean_ci_up_exp,
  mean_nexp,
  mean_ci_lo_nexp,
  mean_ci_up_nexp,
  n_exp,
  n_nexp,
  smd_to_cor = "viechtbauer",
  reverse_means
)

Arguments

mean_exp

mean of participants in the experimental/exposed group.

mean_ci_lo_exp

lower bound of the 95% CI of the mean of the experimental/exposed group

mean_ci_up_exp

upper bound of the 95% CI of the mean of the experimental/exposed group

mean_nexp

mean of participants in the non-experimental/non-exposed group.

mean_ci_lo_nexp

lower bound of the 95% CI of the mean of the non-experimental/non-exposed group.

mean_ci_up_nexp

upper bound of the 95% CI of the mean of the non-experimental/non-exposed group.

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_means

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

Details

This function converts the 95% CI of two independent groups into a standard error, and then relies on the calculations of the es_from_means_se() function.

To convert the 95% CIs into standard errors, the following formula is used (table 12.3 in Cooper):

mean\_se\_exp = \frac{mean\_ci\_up\_exp - mean\_ci\_lo\_exp}{2 * qt{(0.975, df = n\_exp - 1)}}

mean\_se\_nexp = \frac{mean\_ci\_up\_nexp - mean\_ci\_lo\_nexp}{2 * qt{(0.975, df = n\_nexp - 1)}}

Calculations of the es_from_means_se() are then applied.

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 9. Means 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_means_ci(
  n_exp = 55, n_nexp = 55,
  mean_exp = 25, mean_ci_lo_exp = 15, mean_ci_up_exp = 35,
  mean_nexp = 18, mean_ci_lo_nexp = 12, mean_ci_up_nexp = 24
)