es_from_paired_t function

Convert two paired t-test value of two independent groups into several effect size measures

Convert two paired t-test value of two independent groups into several effect size measures

es_from_paired_t( paired_t_exp, paired_t_nexp, n_exp, n_nexp, r_pre_post_exp, r_pre_post_nexp, smd_to_cor = "viechtbauer", reverse_paired_t )

Arguments

  • paired_t_exp: Paired t-test value of the experimental/exposed group.
  • paired_t_nexp: Paired t-test value 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.
  • 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).
  • reverse_paired_t: 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 measureD + G
converted effect size measureOR + R + Z
required input dataSee 'Section 16. Paired: Paired F- or t-test'
https://metaconvert.org/input.html

Details

This function converts paired t-tests of two independent groups value into a Cohen's d (D) and Hedges' g (G) (table 12.2 in Cooper). Odds ratio (OR) and correlation coefficients (R/Z) are then converted from the Cohen's d.

To estimate the Cohen's d, the following formulas are used (Cooper et al., 2019):

cohen_d_exp=paired_t_exp2(1r_pre_post_exp)n_exp cohen\_d\_exp = paired\_t\_exp * \sqrt{\frac{2 * (1 - r\_pre\_post\_exp)}{n\_exp}} cohen_d_nexp=paired_t_nexp2(1r_pre_post_nexp)n_nexp cohen\_d\_nexp = paired\_t\_nexp * \sqrt{\frac{2 * (1 - r\_pre\_post\_nexp)}{n\_nexp}} cohen_d_se_exp=2(1r_pre_post_exp)n_exp+d_exp22n_exp cohen\_d\_se\_exp = \sqrt{\frac{2 * (1 - r\_pre\_post\_exp)}{n\_exp} + \frac{d\_exp^2}{2 * n\_exp}} cohen_d_se_nexp=2(1r_pre_post_nexp)n_nexp+d_nexp22n_nexp cohen\_d\_se\_nexp = \sqrt{\frac{2 * (1 - r\_pre\_post\_nexp)}{n\_nexp} + \frac{d\_nexp^2}{2 * n\_nexp}} cohen_d=d_expd_nexp cohen\_d = d\_exp - d\_nexp d_se=cohen_d_se_exp2+cohen_d_se_nexp2 d\_se = \sqrt{cohen\_d\_se\_exp^2 + cohen\_d\_se\_nexp^2}

To estimate other effect size measures , calculations of the es_from_cohen_d() are applied.

Examples

es_from_paired_t(paired_t_exp = 2.1, paired_t_nexp = 4.2, n_exp = 20, n_nexp = 22)

References

Cooper, H., Hedges, L.V., & Valentine, J.C. (Eds.). (2019). The handbook of research synthesis and meta-analysis. Russell Sage Foundation.

  • Maintainer: Corentin J. Gosling
  • License: GPL (>= 3)
  • Last published: 2025-04-11

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