[R-meta] rma.mv only for better SEs
@|m@h@rme| @end|ng |rom gm@||@com
Mon Jan 31 18:29:19 CET 2022
I have done it, and in my case the results differ. But my point was, is my
explanation regarding why they differ accurate?
On Mon, Jan 31, 2022 at 11:24 AM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:
> Just try it out and you will see what happens.
> >-----Original Message-----
> >From: Simon Harmel [mailto:sim.harmel using 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
> >model has no bearing on the estimates of fixed effects themselves, and
> >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
> >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
> >the average of study-level effects additionally affected by the
> >effects within them.
> >And thus, 1- and 2- may give different overall averages, right?
> >On Mon, Jan 31, 2022 at 11:00 AM Viechtbauer, Wolfgang (SP)
> ><wolfgang.viechtbauer using 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
> >down to the same structure).
> >>-----Original Message-----
> >>From: R-sig-meta-analysis [mailto:
> r-sig-meta-analysis-bounces using 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
> >>their SEs relative to rma()?
> >>Thank you,
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