Compute effect size from Mean and Standard Error.
esc_mean_se( grp1m, grp1se, grp1n, grp2m, grp2se, grp2n, r, es.type = c("d", "g", "or", "logit", "r", "f", "eta", "cox.or", "cox.log"), study = NULL )
grp1m  The mean of the first group. 

grp1se  The standard error of the first group. 
grp1n  The sample size of the first group. 
grp2m  The mean of the second group. 
grp2se  The standard error of the second group. 
grp2n  The sample size of the second group. 
r  Correlation for withinsubject designs (paired samples, repeated measures). 
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 metaanalysis. Thousand Oaks, Calif: Sage Publications
Wilson DB. 2016. Formulas Used by the "Practical MetaAnalysis Effect Size Calculator". Unpublished manuscript: George Mason University
esc_mean_se(grp1m = 7, grp1se = 1.5, grp1n = 50, grp2m = 9, grp2se = 1.8, grp2n = 60, es.type = "or")#> #> Effect Size Calculation for Meta Analysis #> #> Conversion: mean and se to effect size odds ratios #> Effect Size: 0.7468 #> Standard Error: 0.3479 #> Variance: 0.1210 #> Lower CI: 0.3777 #> Upper CI: 1.4769 #> Weight: 8.2634