| esc_bin_prop | R Documentation | 
Compute effect size from binary proportions
esc_bin_prop(
  prop1event,
  grp1n,
  prop2event,
  grp2n,
  es.type = c("logit", "d", "g", "or", "r", "f", "eta", "cox.d"),
  study = NULL
)
| prop1event | Proportion of successes in treatment group (proportion of outcome = yes). | 
| grp1n | Treatment group sample size. | 
| prop2event | Proportion of successes in control group (proportion of outcome = yes). | 
| 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 Unpublished manuscript: George Mason University
# effect size log odds
esc_bin_prop(prop1event = .375, grp1n = 80, prop2event = .47, grp2n = 85)
# effect size odds ratio
esc_bin_prop(prop1event = .375, grp1n = 80, prop2event = .47, grp2n = 85,
             es.type = "or")
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