R/esc_mean_gain.R
esc_mean_gain.Rd
Compute effect size from Mean Gain Scores and Standard Deviations for prepost tests.
esc_mean_gain( pre1mean, pre1sd, post1mean, post1sd, grp1n, gain1mean, gain1sd, grp1r, pre2mean, pre2sd, post2mean, post2sd, grp2n, gain2mean, gain2sd, grp2r, r, es.type = c("d", "g", "or", "logit", "r", "f", "eta", "cox.or", "cox.log"), study = NULL )
pre1mean  The mean of the first group at pretest. 

pre1sd  The standard deviation of the first group at pretest. 
post1mean  The mean of the first group at posttest. 
post1sd  The standard deviation of the first group at posttest. 
grp1n  The sample size of the first group. 
gain1mean  The mean gain between pre and post of the first group. 
gain1sd  The standard deviation gain between pre and post of the first group. 
grp1r  The (estimated) correlation of prepost scores for the first group. 
pre2mean  The mean of the second group at pretest. 
pre2sd  The standard deviation of the second group at pretest. 
post2mean  The mean of the second group at posttest. 
post2sd  The standard deviation of the second group at posttest. 
grp2n  The sample size of the second group. 
gain2mean  The mean gain between pre and post of the second group. 
gain2sd  The standard deviation gain between pre and post of the second group. 
grp2r  The (estimated) correlation of prepost scores for 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
.
For this function, either the gain scores of mean and sd
(gain1mean
and gain1sd
for the first group and
gain2mean
and gain2sd
for the second group) must be
specified, or the prepost values (pre1mean
, post1mean
,
pre1sd
and post1sd
and the counterpart arguments for the
second group).
If the prepost standard deviations are available, no correlation value
grp1r
resp. grp2r
needs to be specified, because these can
then be computed based on tvalue computation. However, if grp1r
is specified, this value will be used (and no ttest performed).
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
# effect size of mean gain scores, with available prepost values esc_mean_gain(pre1mean = 13.07, pre1sd = 11.95, post1mean = 6.1, post1sd = 8.33, grp1n = 78, pre2mean = 10.77, pre2sd = 10.73, post2mean = 8.83, post2sd = 9.67, grp2n = 83)#> #> Effect Size Calculation for Meta Analysis #> #> Conversion: mean gain score to effect size d #> Effect Size: 0.4905 #> Standard Error: 0.3194 #> Variance: 0.1020 #> Lower CI: 0.1356 #> Upper CI: 1.1165 #> Weight: 9.8001# same as above, but with assumed correlation of .5 # Note that effect size is the same, but variance differs esc_mean_gain(pre1mean = 13.07, pre1sd = 11.95, post1mean = 6.1, grp1r = .5, post1sd = 8.33, grp1n = 78, pre2mean = 10.77, pre2sd = 10.73, post2mean = 8.83, post2sd = 9.67, grp2n = 83, grp2r = .5)#>#>#> #> Effect Size Calculation for Meta Analysis #> #> Conversion: mean gain score to effect size d #> Effect Size: 0.4905 #> Standard Error: 0.1600 #> Variance: 0.0256 #> Lower CI: 0.1768 #> Upper CI: 0.8041 #> Weight: 39.0385# effect size based on gain scores for mean and sd. note that the # prepost correlations must be given esc_mean_gain(gain1mean = 1.5, gain1sd = 1, grp1n = 40, grp1r = .5, gain2mean = .7, gain2sd = .8, grp2n = 50, grp2r = .5)#> #> Effect Size Calculation for Meta Analysis #> #> Conversion: mean gain score to effect size d #> Effect Size: 0.8947 #> Standard Error: 0.2224 #> Variance: 0.0494 #> Lower CI: 0.4589 #> Upper CI: 1.3305 #> Weight: 20.2237