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I am doing a meta-analysis in R. I have calculated effect sizes (Cohen's D) for all the studies (17) that qualified my filtering criterion. I want to use random effects model to do my analysis. I tried doing the analysis with metagen() and rma(), both returning completely different results (Copy-pasted below). I’m wondering if what I’m doing is correct? Is there another way to do the meta-analysis? Will really appreciate any help of guidance. Result for meta-gen:

                                       95%-CI     z  p-value
Fixed effect model   0.3687 [ 0.3385; 0.3990] 23.90 < 0.0001
Random effects model 0.0345 [-0.2560; 0.3249]  0.23   0.8160

Quantifying heterogeneity:

tau^2 = 0.3437; H = 8.16 [7.37; 9.03]; I^2 = 98.5% [98.2%; 98.8%]

Test of heterogeneity:

       Q d.f.  p-value
 1065.79   16 < 0.0001

Details on meta-analytical method: - Inverse variance method - DerSimonian-Laird estimator for tau^2

Result for rma():

Random-Effects Model (k = 17; tau^2 estimator: REML)

tau^2 (estimated amount of total heterogeneity): 1.2737 (SE = 0.4612)
tau (square root of estimated tau^2 value):      1.1286
I^2 (total heterogeneity / total variability):   99.59%
H^2 (total variability / sampling variability):  244.16

Test for Heterogeneity: 
Q(df = 16) = 1065.7913, p-val < .0001

Model Results:

estimate      se    zval    pval    ci.lb   ci.ub   
  0.0332  0.2770  0.1200  0.9045  -0.5097  0.5762
Random Cotija
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  • Welcome to SO. There are way too few details in your post for others to be able to offer any meaningful help. Where is your data? What are you modelling? And how? Posting the model fitting output is entirely pointless without those details. The devil is in the detail! Please review [how to ask](https://stackoverflow.com/help/how-to-ask) questions here on SO, and then provide a [minimal reproducible example/attempt](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example), including sample data. – Maurits Evers Jul 02 '18 at 10:09
  • You should include a reproducible example. Try for instance the meta package , you can find the Olkin95 dataset for binomial data and Fleiss93cont for continuous data. – paoloeusebi Nov 01 '18 at 22:51

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