es_from_means_se_pre_post function

Convert pre-post means of two independent groups into various effect size measures

es_from_means_se_pre_post(
  mean_pre_exp,
  mean_exp,
  mean_pre_se_exp,
  mean_se_exp,
  mean_pre_nexp,
  mean_nexp,
  mean_pre_se_nexp,
  mean_se_nexp,
  n_exp,
  n_nexp,
  r_pre_post_exp,
  r_pre_post_nexp,
  smd_to_cor = "viechtbauer",
  pre_post_to_smd = "bonett",
  reverse_means_pre_post
)

Arguments

• mean_pre_exp: mean of the experimental/exposed group at baseline
• mean_exp: mean of the experimental/exposed group at follow up
• mean_pre_se_exp: standard error of the experimental/exposed group at baseline
• mean_se_exp: standard error of the experimental/exposed group at follow up
• mean_pre_nexp: mean of the non-experimental/non-exposed group at baseline
• mean_nexp: mean of the non-experimental/non-exposed group at follow up
• mean_pre_se_nexp: standard error of the non-experimental/non-exposed group at baseline
• mean_se_nexp: standard error of the non-experimental/non-exposed group at follow up
• n_exp: number of the experimental/exposed group
• n_nexp: number of the non-experimental/non-exposed group
• r_pre_post_exp: pre-post correlation in the experimental/exposed group
• r_pre_post_nexp: pre-post correlation in the non-experimental/non-exposed group
• smd_to_cor: formula used to convert the cohen_d value into a coefficient correlation (see details).
• pre_post_to_smd: formula used to convert the pre and post means/SD into a SMD (see details).
• reverse_means_pre_post: a logical value indicating whether the direction of generated effect sizes should be flipped.

Returns

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 15. Paired: pre-post means and dispersion'
	https://metaconvert.org/input.html

Details

This function converts the pre/post standard errors of two independent groups into standard deviations (Section 6.5.2.2 in the Cochrane Handbook).

$$mean\_pre\_sd\_exp = mean\_pre\_se\_exp * \sqrt{n\_exp}$$ $$mean\_pre\_sd\_nexp = mean\_pre\_se\_nexp * \sqrt{n\_nexp}$$ $$mean\_sd\_exp = mean\_se\_exp * \sqrt{n\_exp}$$ $$mean\_sd\_nexp = mean\_se\_nexp * \sqrt{n\_nexp}$$

Then, calculations of the es_from_means_sd_pre_post() are applied.

Examples

es_from_means_sd_pre_post(
  n_exp = 36, n_nexp = 35,
  mean_pre_exp = 98, mean_exp = 102,
  mean_pre_sd_exp = 16, mean_sd_exp = 17,
  mean_pre_nexp = 96, mean_nexp = 102,
  mean_pre_sd_nexp = 14, mean_sd_nexp = 15,
  r_pre_post_exp = 0.8, r_pre_post_nexp = 0.8
)

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.