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

Whether this makes sense or not depends on how we believe covariances
among the sampling errors are arising. Two estimates from the same study
based on the same sample of subjects (e.g., based on two different response
variables) probably have correlated sampling errors. Two estimates from the
same study, one for female, the other for male participants, not (the
underlying true effects may still be correlated). So, the 'cluster'
variable should be specified accordingly (i.e., same levels for the two
estimates in the first case, different levels for the two estimates in the
second case; i.e., 1, 1, 2, 3).

-----Original Message-----
From: Simon Harmel [mailto:sim.harmel at gmail.com]
Sent: Thursday, 18 March, 2021 12:53
To: Viechtbauer, Wolfgang (SP)
Cc: R meta
Subject: Re: [R-meta] Multivariate meta-analysis when "some studies" are

multi-

outcome

Dear Wolfgang,

Many thanks for your response. The reason I asked which level of

dependence does V

matrix account for was that I realized (at least when using
'impute_covariance_matrix()' function) that always the highest cluster

level

(e.g., study_id rather than outcome_id or es_id) is used to construct the

V

matrix.

So, is there a reason for that?

Many thanks

On Thu, Mar 18, 2021, 6:38 AM Viechtbauer, Wolfgang (SP)
<wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
Dear Simon,

Roughly, whatever you put into 'random' accounts for heterogeneity in the

true

effects (at possibly multiple levels) and can account for possible

dependencies in

these true effects. Whatever you put into V accounts for the sampling

variances in

the estimates or more precisely, their sampling errors, and can account

for

possible dependencies in these sampling errors.

I use the term 'dependencies' in a very vague/broad sense here, since such
dependencies (in the true effects and/or the sampling errors) can arise

for all

kinds of different reasons.

Best,
Wolfgang

-----Original Message-----
From: Simon Harmel [mailto:sim.harmel at gmail.com]
Sent: Wednesday, 17 March, 2021 18:01
To: Viechtbauer, Wolfgang (SP)
Cc: Gladys Barragan-Jason; R meta
Subject: Re: [R-meta] Multivariate meta-analysis when "some studies" are

multi-

outcome

Dear Wolfgang,

I do want to quickly follow-up on the answer you linked
(

https://stat.ethz.ch/pipermail/r-sig-meta-analysis/2018-July/000896.html).

In `rma.mv(y ~ x1 + x2, V, random = ~ 1 | study/outcome/id,

data=data)`, we

apparently take into account dependence among effect sizes due to

multiple

treatments (`id`), and multiple outcomes (`outcome`) by means of using a

level

for

each.

If so, what is the role of `V` when it comes to accounting for effect
size dependency? Does `V` simply determine the pair-wise structure of

effect size

dependency? If yes, at what level?

Simon