[R-meta] Multi-level meta-analysis: large sigma^2

Juan Gallego Zamorano j@g@||ego@z@mor@no @end|ng |rom gm@||@com
Wed Nov 24 14:31:49 CET 2021

Dear meta-analysis list subscribers,

I am conducting a multi-level meta-analysis for which I am using the log
response ratio (logRR or ratio of means) as an outcome effect. I have
several comparisons within a common control for some studies so I
calculated a variance-covariance matrix and included it in the V argument.
Because my dataset is hierarchical, I included the individual IDs for the
logRR nested within the ID of the Source (papers) in the random effect
structure to account for between observation variability. The model runs
well and the profile plots look good, however, I'm a bit surprised by the
value of the sigma^2 for the individual logRR which is extremely high
compared to the Source one (see below the summary of the model) and the I^2
are also very high (~99% for the Source/RowID and ~1% for the Source only).
Therefore, I would like to ask:
1) Is this normal? I feel that this is way too high and maybe there is
something that I am missing and needs correction but I do not know what.
2) If it is not normal, how can I check what is going on? As I said I run
the profile plots and they are fine but I am not sure what else I can check.

Multivariate Meta-Analysis Model (k = 1839; method: REML)
Variance Components:
            estim    sqrt  nlvls  fixed        factor
sigma^2.1  0.0515  0.2269     62     no        Source
sigma^2.2  5.0483  2.2468   1839     no  Source/RowID

Test for Heterogeneity:
Q(df = 1838) = 100501.9124, p-val < .0001

Model Results:
estimate      se    zval    pval   ci.lb   ci.ub
  0.2772  0.0720  3.8518  0.0001  0.1361  0.4182  ***

Thanks a lot in advance!



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