13.2 Calculating Hedges’ g from a regression coefficient

13.2.1 Unstandardized regression coefficients

It is also possible to calculate Hedges’ g from an unstandardized or standardized regression coeffiecent (Lipsey and Wilson 2001).

For unstardardized coefficients, we can use the esc_B function with the following parameters:

  • b: unstandardized coefficient \(b\) (the “treatment” predictor).
  • sdy: the standard deviation of the dependent variable \(y\) (i.e., the outcome).
  • grp1n: the number of participants in the first group.
  • grp2n: the number of participants in the second group.
  • es.type: the effect measure we want to calculate. In our case this is "g". But we could also calculate Cohen’s d using "d".



Here’s an example

esc_B(b=3.3,sdy=5,grp1n = 100,grp2n = 150,es.type = "g")
## 
## Effect Size Calculation for Meta Analysis
## 
##      Conversion: unstandardized regression coefficient to effect size Hedges' g
##     Effect Size:   0.6941
##  Standard Error:   0.1328
##        Variance:   0.0176
##        Lower CI:   0.4338
##        Upper CI:   0.9544
##          Weight:  56.7018



13.2.2 Standardized regression coefficents

Here, we can use the esc_beta function with the follwing parameters:

  • beta: standardized coefficient \(\beta\) (the “treatment” predictor).
  • sdy: the standard deviation of the dependent variable \(y\) (i.e., the outcome).
  • grp1n: the number of participants in the first group.
  • grp2n: the number of participants in the second group.
  • es.type: the effect measure we want to calculate. In our case this is "g". But we could also calculate Cohen’s d using "d".



Here’s an example

esc_beta(beta=0.7, sdy=3, grp1n=100, grp2n=150, es.type = "g")
## 
## Effect Size Calculation for Meta Analysis
## 
##      Conversion: standardized regression coefficient to effect size Hedges' g
##     Effect Size:   1.9868
##  Standard Error:   0.1569
##        Variance:   0.0246
##        Lower CI:   1.6793
##        Upper CI:   2.2942
##          Weight:  40.6353

References

Lipsey, Mark W, and David B Wilson. 2001. Practical Meta-Analysis. Sage Publications, Inc.

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