[R-meta] SEM of correlational meta-analytic data?

Viechtbauer, Wolfgang (SP) wo||g@ng@v|echtb@uer @end|ng |rom m@@@tr|chtun|ver@|ty@n|
Sun Jan 17 12:11:14 CET 2021

Dear Gladys,

Inferring causality from observational data is tricky business. SEM (with primary data) or meta-analytic structural equation modeling (MASEM) does not magically allow us to do so just by fitting some model.

But if you want to do MASEM, then the MetaSEM package is a good choice. I also recently added some functionality to metafor that goes a bit in the same direction. See:


Note that you will need to install the 'devel' version of metafor to make use of these functions:



>-----Original Message-----
>From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org]
>On Behalf Of Gladys Barragan-Jason
>Sent: Sunday, 17 January, 2021 11:23
>To: r-sig-meta-analysis using r-project.org
>Subject: [R-meta] SEM of correlational meta-analytic data?
>Dear all,
>I am conducting a meta-analysis on the causes and consequences of
>human-nature connectedness. As most of the studies were correlational, I
>collected zero order Pearson r correlations between HNC and let's say 3
>moderators (Exposure to nature, human-welfare and nature conservation). I
>was able to obtain positive and moderate estimates in running one model by
>moderator with lab and study as random effect thanks to the rma.mv
>function which was great.
>My only concern now if whether we could somehow infer causality from those
>meta-analytic data in making Structural Equation Modelling (SEM) on those
>data. I saw that the MetaSEM package can do so but I have the feeling that
>it is not using the same structure/function as metafor (e.g. meta3 instead
>of rma.mv) leading to some discrepancies.
>I would like to know if someone has developed a package or a function to do
>this type of causal analysis from meta-analytic correlation data.
>The aim would be validate (or invalidate) a model where exposure to nature
>increases HNC which in turn increases Nature conservation and welfare
>(rather than the opposite). I don(t know if it is feasible but would be
>great if so.
>Any advice would be more than welcome :-)
>All the best,

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