-----Original Message-----
From: Simon Harmel [mailto:sim.harmel at gmail.com]
Sent: Monday, 31 January, 2022 18:21
To: Viechtbauer, Wolfgang (SP)
Cc: R meta
Subject: Re: [R-meta] rma.mv only for better SEs
Thank you, Wolfgang. I asked this, because I noticed?applying RVE to an rma.mv()
model has no bearing on the estimates of fixed effects themselves, and just
modifies their SEs.
So, I wondered if the same rule, at least "in principle", should apply when we go
from rma() to rma.mv().
But is there a principle?regarding how random effects affect the fixed effects?
For instance, in:
1- rma.mv(y ~ 1, random = ~ 1|study/obs), the overall average only represents the
average of study-level effects.
But, in:
2- rma.mv(y ~ 1, random = ~ 1|study/outcome/obs), the overall average represents
the average of study-level effects additionally affected by the outcome-level
effects within them.
And thus, 1- and 2- may give different overall averages, right?
Simon
On Mon, Jan 31, 2022 at 11:00 AM Viechtbauer, Wolfgang (SP)
<wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
Generally, two models with different random effects structures will also give you
different estimates of the fixed effects (unless the estimates of the
variance/covariance components happen to be such that the two models collapse
down to the same structure).
Best,
Wolfgang
-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org] On
Behalf Of Simon Harmel
Sent: Monday, 31 January, 2022 17:49
To: R meta
Subject: [R-meta] rma.mv only for better SEs
Hello List Members,
Reviewing the archived posts, my understanding is that my studies can
produce multiple effects, so I should use rma.mv() not rma().
Also, I understand rma.mv() ensures that I get more accurate SEs for my
fixed effects relative to rma().
BUT does that also mean that, by definition, rma.mv() should have no
bearing on the magnitude of the fixed effects themselves and only modifies
their SEs relative to rma()?
Thank you,
Simon