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

[Juan Gallego Zamorano]

Hi James,

Thanks a lot for the suggestion. I actually explored that before the
analysis, but I'm going to double/triple check. The main problem is that I
have some 0s both in the means and the SDs. I corrected the means following
your 2015 and 2018 papers, and the SDs I imputed them using Bracken 1992
method. Probably the problem is there and I need to explore other
imputation options.
Thanks again,

Juan

On Wed, 24 Nov 2021 at 18:09, James Pustejovsky <jepusto using gmail.com> wrote:

> Hi Juan,
>
> I would guess that you probably have one or more outliers in your data
> that need to be checked. Plot your data using a forest plot or even
> just a histogram of the logRR values to find the outliers. Then double
> check that the values actually make sense (or whether there might be
> typos or something).
>
> James
>
> On Wed, Nov 24, 2021 at 7:33 AM Juan Gallego Zamorano
> <j.gallego.zamorano using gmail.com> wrote:
> >
> > 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!
> >
> > Best,
> >
> > Juan
> >
> >         [[alternative HTML version deleted]]
> >
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