[R-meta] rma.mv only for better SEs

[Viechtbauer, Wolfgang (SP)]

The random effects structure determines the weight matrix, which in turn affects the estimates of the random effects.

Best,
Wolfgang

>-----Original Message-----
>From: Simon Harmel [mailto:sim.harmel using gmail.com]
>Sent: Monday, 31 January, 2022 18:29
>To: Viechtbauer, Wolfgang (SP)
>Cc: R meta
>Subject: Re: [R-meta] rma.mv only for better SEs
>
>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.
>
>Best,
>Wolfgang
>
>>-----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 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 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 collapse
>>down to the same structure).
>>
>>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: 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