esc_mean_sd {esc}  R Documentation 
Compute effect size from mean and either groupbased standard deviations or full sample standard deviation.
esc_mean_sd( grp1m, grp1sd, grp1n, grp2m, grp2sd, grp2n, totalsd, r, es.type = c("d", "g", "or", "logit", "r", "cox.or", "cox.log"), study = NULL )
grp1m 
The mean of the first group. 
grp1sd 
The standard deviation of the first group. 
grp1n 
The sample size of the first group. 
grp2m 
The mean of the second group. 
grp2sd 
The standard deviation of the second group. 
grp2n 
The sample size of the second group. 
totalsd 
The full sample standard deviation. Either 
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 Unpublished manuscript: George Mason University
# with standard deviations for each group esc_mean_sd( grp1m = 7, grp1sd = 2, grp1n = 50, grp2m = 9, grp2sd = 3, grp2n = 60, es.type = "logit" ) # effectsize d, withinsubjects design esc_mean_sd( grp1m = 7, grp1sd = 2, grp1n = 50, grp2m = 9, grp2sd = 3, grp2n = 60, r = .7 ) # with full sample standard deviations esc_mean_sd(grp1m = 7, grp1n = 50, grp2m = 9, grp2n = 60, totalsd = 4)