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

Viechtbauer Wolfgang (SP) wolfgang.viechtbauer at maastrichtuniversity.nl
Sun Mar 25 11:49:33 CEST 2018

If you want to pass a pooled correlation matrix to some kind of software for SEM and one of the cells is NA, then indeed, this won't work. Depending on the model you are trying to fit, certain cells may actually not be needed, but I don't know any software for SEM that will work with a covariance/correlation matrix with missing cells.


-----Original Message-----
From: Jens Schüler [mailto:jens.schueler at wiwi.uni-kl.de] 
Sent: Saturday, 24 March, 2018 20:57
To: Viechtbauer Wolfgang (SP); r-sig-meta-analysis at r-project.org
Subject: AW: Handling dependencies among multiple independent and dependent variables

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?


More information about the R-sig-meta-analysis mailing list