[R-meta] Handling dependencies among multiple independent and dependent variables

[Mike Cheung]

Dear Jens,

This is a misconception. There is no such requirement that at least one
study has to include all variables. You may refer to Cheung (in press, p.
4, footnote 2) https://psyarxiv.com/37p2z .

Both the fixed- and random-effects models in the tssem1() function in the
metaSEM package handle data well without a study with complete data. That
said, there may be other issues if the studies are not from "similar
populations."

Best,
Mike

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 Mike W.L. Cheung               Phone: (65) 6516-3702
 Department of Psychology       Fax:   (65) 6773-1843
 National University of Singapore
 http://mikewlcheung.github.io/
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*Jens Schüler* jens.schueler at wiwi.uni-kl.de
<r-sig-meta-analysis%40r-project.org?Subject=Re:%20Re%3A%20%5BR-meta%5D%20Handling%20dependencies%20among%20multiple%20independent%20and%0A%20dependent%20variables&In-Reply-To=%3CE8B2892D8B77104FA4A245B3CCBCBA2BFEAB75%40EXMBX06.rhrk.uni-kl.de%3E>
*Sat Mar 24 20:57:07 CET 2018*


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------------------------------

Dear Wolfgang,

thank you very much for the detailed explanation.
I just have to rearrange the coding sheet a bit and I am good to go. The
project we are working on is actually a MASEM and I am currently tackling
the stage of pooling the correlation matrix. However, we are not using the
TSSEM approach of Cheung but follow the “old” approach of Viswesvaran &
Ones, 1995.

I would like to raise a quick question concerning the applicability of the
TSSEM approach. I am not sure whether Cheung stated it himself, in one of
his articles or book, but others (e.g. Landis 2013; doi
10.1007/s10869-013-9285-x) argued that TSSEM can only be used if at least
one study provides full information – which is not the case in our project.
Is this really a “hard/must” requirement or what would be the risk/danger if
TSSEM is used nevertheless in such a scenario?


Best
Jens

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