Compute effect size from Standardized Regression Coefficient.
esc_beta( beta, sdy, grp1n, grp2n, es.type = c("d", "g", "or", "logit", "r", "f", "eta", "cox.or", "cox.log"), study = NULL )
beta | The standardized beta coefficient. |
---|---|
sdy | The standard deviation of the dependent variable. |
grp1n | Treatment group sample size. |
grp2n | Control group sample size. |
es.type | Type of effect size that should be returned.
|
study | Optional string with the study name. Using |
The effect size es
, the standard error se
, the variance
of the effect size var
, the lower and upper confidence limits
ci.lo
and ci.hi
, the weight factor w
and the
total sample size totaln
.
If es.type = "r"
, Fisher's transformation for the effect size
r
and their confidence intervals are also returned.
Lipsey MW, Wilson DB. 2001. Practical meta-analysis. Thousand Oaks, Calif: Sage Publications
Wilson DB. 2016. Formulas Used by the "Practical Meta-Analysis Effect Size Calculator". Unpublished manuscript: George Mason University
esc_beta(.7, 3, 100, 150)#> #> Effect Size Calculation for Meta Analysis #> #> Conversion: standardized regression coefficient to effect size d #> Effect Size: 1.9928 #> Standard Error: 0.1569 #> Variance: 0.0246 #> Lower CI: 1.6853 #> Upper CI: 2.3003 #> Weight: 40.6353esc_beta(.7, 3, 100, 150, es.type = "cox.log")#> #> Effect Size Calculation for Meta Analysis #> #> Conversion: standardized regression coefficient to effect size Cox logits #> Effect Size: 3.2881 #> Standard Error: 0.2589 #> Variance: 0.0671 #> Lower CI: 2.7806 #> Upper CI: 3.7956 #> Weight: 14.9132