[R-meta] 3-level meta with robust errors

James Pustejovsky jepu@to @end|ng |rom gm@||@com
Tue Dec 1 19:10:02 CET 2020


These are indeed perplexing results. Based on the information you've
provided, it's hard to say what could be going on. Could you provide
examples of the code you're using and the results of your analyses? Doing
so will help to identify potential problems or coding errors.

Kind Regards,

On Tue, Dec 1, 2020 at 10:45 AM Valeria Ivaniushina <v.ivaniushina using gmail.com>

> Dear list members,
> We are conducting several meta-analyses using the metafor package in R
> (Viechtbauer 2010) because of 3-level data structure, followed by
> sandwich-type estimator with a small-sample adjustment to get cluster
> robust standard errors.
> There are some things that puzzle me, and I hope to get answers from the
> community.
> 1. We calculate 95% CI for our mean effect size, and p-value is calculated
> as a part of the output. While CI always indicate significant mean effect
> size, p-values are often > 0.05
> - Should I report both CI and p-value?
> - How to interpret such discrepancy?
> 2. When I draw a forest plot for a meta-analysis of 8 models, I can see
> that 95% CIs for every coefficient contain zero (for example, -0.40 -
> 0.84). However, the 95% CI for the mean coefficient is well above zero
> (0,28 - 0,45).  How is it possible?
> 3.  Theoretically, the data has a 3-level structure (model; article;
> database). But sometimes I see that there is no variance on one or two of
> the levels. Should I repeat the analysis with only 2 or 1 level, according
> to the variance distribution?
> Best, Valeria
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