[R-meta] 4-Level analysis in metafor

Harris, Jordan L jord@n-|-h@rr|@ @end|ng |rom u|ow@@edu
Fri Mar 4 17:29:55 CET 2022

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!

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