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

Jens Schüler jens.schueler at wiwi.uni-kl.de
Tue Mar 6 14:50:20 CET 2018

Hi all,


I am currently working on a meta-analysis on strategic orientations (IV) and
firm performance (DV), using correlational data, and struggle with how I
should best handle dependencies among effect sizes.


Short elaboration of the issue:

The strategic orientation I am interested in consists of three subdimensions
and some studies report correlational data between the subdimensions and
e.g. profitability, whereas other studies report only a correlation between
the whole construct and profitability. Moreover, some studies use more than
one profitability measure. I am interested in the overall aggregate effect
between the “whole” strategic orientation and “whole” profitability.


This leaves me with the following cases:

1. Whole orientation and single profitability measure (trivial)

2. Whole orientation and multiple profitability measures

3. Multiple dimensions and single profitability measure

4. Multiple dimensions and multiple profitability measures 


Following the mailing list and the metaphor website, I could handle the 2nd
case through nesting the multiple effects in studies and using the
impute_covariance_matrix function of the clubSandwhich package. However, I
am not exactly sure on how to appropriately handle case 3 and 4 and
especially, how to combine 2 to 4 in order to run the analysis on the
aggregate level (whole orientation – whole profitability).


Due to working with correlations, the respective studies report the
correlations between the variables e.g. between the dimensions, between the
profitability measures and the correlations between the dimensions and
profitability measures.





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