[R-meta] Computing var-covariance matrix with correlations of six non-independent outcomes

James Pustejovsky jepu@to @end|ng |rom gm@||@com
Tue Jul 7 18:54:10 CEST 2020

Hi Mika,

To add to Wolfgang's question, could you tell us a little bit more about
how you have structured the data on correlations between types of
motivation? Is it just one correlation matrix (6X6 matrix, with 1 + 2 + 3 +
4 + 5 = 15 unique correlations)? Or is it study-specific?

This sort of calculation is a bit tricky to carry out so I am not surprised
that you haven't found a solution in the listserv archives. If you are
willing to share your dataset (or a subset thereof, say 3-4 studies worth
of data), it may make it easier for us to help problem solve.


On Tue, Jul 7, 2020 at 11:42 AM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:

> Dear Mika,
> What effect size measure are you using for the meta-analysis?
> Best,
> Wolfgang
> >-----Original Message-----
> >From: R-sig-meta-analysis [mailto:
> r-sig-meta-analysis-bounces using r-project.org]
> >On Behalf Of Mika Manninen
> >Sent: Tuesday, 07 July, 2020 18:10
> >To: r-sig-meta-analysis using r-project.org
> >Subject: [R-meta] Computing var-covariance matrix with correlations of six
> >non-independent outcomes
> >
> >Hello,
> >
> >I am doing a meta-analysis looking at the effect of a teaching
> intervention
> >(versus control) on six types of motivation/behavioral regulation.
> >Theoretically and empirically these constructs form a continuum in which
> >the continuum neighbors are most strongly positively correlated and the
> >furthest from one another most negatively correlated.
> >
> >I have 95 effects. These effects come from 25 studies, each reporting
> >scores for between 1-6 motivation types. The number of effects per
> >motivation ranges from 22 to 13. In some studies, they have measured only
> >one or two types whereas in others they have measured 5 or all 6 types of
> >motivation.
> >
> >I originally ran a separate random-effects meta-analysis for all the six
> >outcomes. However, I got feedback that the dependency of the motivation
> >types should be taken into account and a 3-level meta-analysis was
> >recommended. After looking into it, the 3-level model seems to be a worse
> >approach than the multivariate approach.
> >
> >As is not usually the case, I have succeeded in gathering all correlations
> >between all the motivation types for all studies (some from original
> >reporting and some from previous meta-analysis findings).
> >
> >My question is, how do I compute the V-matrix for this data in order to
> run
> >the multivariate analysis? I read the whole archive but I could not find a
> >clear answer to the problem.
> >
> >Thank you very much in advance,
> >
> >Mika
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