es_from_beta_std function

Convert a standardized regression coefficient and the standard deviation of the dependent variable into several effect size measures

es_from_beta_std(
  beta_std,
  sd_dv,
  n_exp,
  n_nexp,
  smd_to_cor = "viechtbauer",
  reverse_beta_std
)

Arguments

• beta_std: a standardized regression coefficient value (binary predictor, no other covariables in the model)
• sd_dv: standard deviation of the dependent variable
• 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_beta_std: a logical value indicating whether the direction of the generated effect sizes should be flipped.

Returns

This function estimates and converts between several effect size measures.

natural effect size measure	D + G
converted effect size measure	OR + R + Z
required input data	See 'Section 13. (Un-)Standardized regression coefficient'
	https://metaconvert.org/input.html

Details

This function converts a standardized linear regression coefficient (coming from a model with only one binary predictor), into an unstandardized linear regression coefficient.

$$sd\_dummy = \sqrt{\frac{n_exp - (n_exp^2 / (n_exp + n_nexp))}{(n_exp + n_nexp - 1)}}$$ $$unstd\_beta = beta\_std * \frac{sd\_dv}{sd\_dummy}$$

Calculations of the es_from_beta_unstd functions are then used.

Examples

es_from_beta_std(beta_std = 2.1, sd_dv = 0.98, n_exp = 20, n_nexp = 22)

References

Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. Sage Publications, Inc.