Is the formula used for esc package and comprehensive meta-analysis software different?

[Elie-Yu]

I noticed there are different results when calculating effect size with information available for both treatment and control groups on sample size and the mean and SD for pretest and posttest. this comparison is between using the esc package and comprehensive meta-analysis software.

An example of data and script that I used is

In esc package: esc_mean_gain(pre1mean = 3.34, pre1sd = 1.76, post1mean = 3.28, post1sd = 2.07, grp1n = 34, pre2mean = 3.81, pre2sd = 1.79, post2mean = 8.43, post2sd = 0.83, grp2n = 34, es.type = "g") The results returns g= 2.755 var(g) = 0.3114

Using the same values in Comprehensive Meta-analysis, the results returned as follows: g= 2.9338 var(g) = 0.343

I wonder if different formula is used. Could you help me understand what leads to the difference and what results to choose from?

[Elie-Yu]

To follow up, I also did the calculation in "Practical Meta-Analysis Effect Size Calculator"

using different SDs:

ets/140570906/3d218406-8e25-4531-b04d-8424795b160f">

[badgettrg]

I have the same problem with esc_mean_gain. Below is the R studio code and output (which produces NaNs except for the SE. Below that is the web-based output. Thanks much; great package! bob

In R Studio I get:

Gordon2_JC_Challenges <- esc_mean_gain(

CONTROL

pre1mean = 3.29, pre1sd = 0.77, post1mean = 3.20, post1sd = 0.63, grp1n = 26, #grp1r = 0.5,

EXPERIMENTAL

pre2mean = 3.23, pre2sd = 0.70, post2mean = 3.23, post2sd = 0.64, grp2n = 32, es.type = "d", study = "Gordon(2), 2018" )

Gordon(2), 2018 (n=58)

 Conversion: mean gain score to effect size d
Effect Size:   0.1313

Standard Error: NaN Variance: NaN Lower CI: NaN Upper CI: NaN Weight: NaN