Compute effect size from One-way Anova with two independent groups.
esc_f( f, totaln, grp1n, grp2n, es.type = c("d", "g", "or", "logit", "r", "f", "eta", "cox.or", "cox.log"), study = NULL )
f | The F-value of the F-test. |
---|---|
totaln | Total sample size. Either |
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
.
This function only applies to one-way Anova F-tests with
two independent groups, either equal or unequal sample sizes.
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 Unpublished manuscript: George Mason University
# unequal sample size esc_f(f = 5.5, grp1n = 100, grp2n = 150)#> #> Effect Size Calculation for Meta Analysis #> #> Conversion: F-value (one-way-Anova) to effect size d #> Effect Size: 0.3028 #> Standard Error: 0.1298 #> Variance: 0.0169 #> Lower CI: 0.0483 #> Upper CI: 0.5572 #> Weight: 59.3472# equal sample size esc_f(f = 5.5, totaln = 200)#> #> Effect Size Calculation for Meta Analysis #> #> Conversion: F-value (one-way-Anova) to effect size d #> Effect Size: 0.3317 #> Standard Error: 0.1424 #> Variance: 0.0203 #> Lower CI: 0.0526 #> Upper CI: 0.6107 #> Weight: 49.3218