[R-meta] Multivariate meta-analysis when "some studies" are multi-outcome

[Simon Harmel]

Dear Prof. Viechtbauer,

Many thanks for your response. I found the following particularly helpful (
https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2019-March/001484.html).

So, I went from my initial model: `rma.mv(d, V = SE^2, mods =
~factor(outcome)-1, random= ~1|id, data = dat)`
to now:

`V <- clubSandwich::impute_covariance_matrix(vi = dat$SE^2, cluster =
dat$id, r = 0.7)`
`rma.mv(d, V = V, mods = ~factor(outcome)-1, random= ~1|id, data = dat)`

However, what type of dependence is accounted for by the multilevel part
(i.e., `random= ~1|id`), and what type of dependence is accounted for by
including the imputed variance-covariance matrix?

Specifically, in my data, all primary studies (n=52) are longitudinal, 15
of them are multi-outcome, and almost all are multi-group treatments. Are
all of these types of dependence reasonably accounted for?

Many thanks for your consideration,
Simon

On Mon, Mar 15, 2021 at 6:54 AM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:

> Hi Simon,
>
> I would suggest to search/browse the archives, as this kind of question
> has been discussed at various points in the past. The archives can be found
> here:
>
> https://stat.ethz.ch/pipermail/r-sig-meta-analysis/
>
> There is no built-in search functionality for the archives, but one can
> restrict search engines to conduct searches at particular sites. For
> example, if you do a google search including
>
> site:https://stat.ethz.ch/pipermail/r-sig-meta-analysis/
>
> you should only get 'hits' from the mailing list archives. The same should
> work with DuckDuckGo. Note sure about other engines.
>
> Note that search engines index the archives at semi-regular intervals, so
> the most recent posts will not show up this way, but those can be searched
> manually.
>
> Best,
> Wolfgang
>
> >-----Original Message-----
> >From: R-sig-meta-analysis [mailto:
> r-sig-meta-analysis-bounces using r-project.org] On
> >Behalf Of Simon Harmel
> >Sent: Saturday, 13 March, 2021 23:53
> >To: R meta
> >Subject: [R-meta] Multivariate meta-analysis when "some studies" are
> multi-outcome
> >
> >Dear All,
> >
> >I'm conducting a meta-analysis where 15 out of 52 studies have used more
> >than one outcome variable. In addition, almost all studies include
> multiple
> >treatments.
> >
> >A shortened version (i.e., without moderators) of our dataset appears
> below
> >(`*id`=study id; `d`=effect size; `SE` = standard error; `outcome`=outcome
> >variable index*).
> >
> >I was wondering what would be the appropriate modeling options for such a
> >situation?
> >
> >I appreciate your expertise and consideration,
> >Simon
> >
> >*#-- R data and code:*
> >dat <- read.csv("https://raw.githubusercontent.com/hkil/m/master/tst.csv
> ")
> >
> >library(metafor)
> >rma.mv(d, V = SE^2, mods = ~factor(outcome)-1, random= ~1|id, data = dat)
> >## I'm assuming this would be an insufficient model
>

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