________________________________________
From: Viechtbauer, Wolfgang (SP) <wolfgang.viechtbauer at maastrichtuniversity.nl>
Sent: Friday, March 4, 2022 10:56 AM
To: Harris, Jordan L <jordan-l-harris at uiowa.edu>; r-sig-meta-analysis at r-
project.org <r-sig-meta-analysis at r-project.org>
Subject: [External] RE: 4-Level analysis in metafor
Hi Jordan,
Sure it can. We have done 5-level models (including another crossed random
effect) with rma.mv():
https://wviechtb.github.io/metadat/reference/dat.mccurdy2020.html
How well the variance components can be estimated depends of course on how much
data you have. And it can certainly happen that one components ends up being
estimated to be (close to) zero.
I wouldn't bother removing that one level - that happens implicitly/automatically
when a variance component is estimated to be 0.
Best,
Wolfgang
-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org] On
Behalf Of Harris, Jordan L
Sent: Friday, 04 March, 2022 17:30
To: r-sig-meta-analysis at r-project.org
Subject: [R-meta] 4-Level analysis in metafor
Hi all,
Does rma.mv appropriately account for between- and within-cluster variance for 4
level nested data?
rma.mv(yi=ES, V=sampling_variance, slab=authors, data=Data, random = list(~ 1 |
datasource_id/wave_id/study), tdist=TRUE, method="REML")
study_id = included study
datasource = the source of data (e.g., large cohort study or independent
samples)
wave_id = the wave of the datasource (i.e., age) from which the study was
analyzed
Multiple effect sizes can occur at a given wave in a given data source. Multiple
effect sizes also exist in a given study at a given wave. Provided this
information, it might be important to nest studies within waves within data
sources. I ask because I see that the sigma^2.2. estimate of my output is nearly
0 and I was not sure if this is an accurate reflection of my data or metafor's
ability to account for differences at this added level? Should I use the 0
estimate at 2.2 to justify a removal of wave_id from the nesting?
Multivariate Meta-Analysis Model (k = 100; method: REML)
Variance Components:
??????????? estim??? sqrt? nlvls? fixed????????????????????????? factor
sigma^2.1? 0.0069? 0.0832???? 41???? no?????????????????? datasource_id
sigma^2.2? 0.0000? 0.0000???? 60???? no?????????? datasource_id/wave_id
sigma^2.3? 0.0023? 0.0482???? 82???? no? datasource_id/wave_id/study_id
I am a graduate student, and I am new to meta-analyses, and I would love any
feedback!
Thanks,
Jordan