[R-meta] Quick question about multiple independent samples within one study

James Pustejovsky jepu@to @ending from gm@il@com
Thu Dec 13 16:35:16 CET 2018


I agree with Wolfgang's suggestion to fit a three-level random effects
model. A small additional suggestion: to directly answer the question you
posed, you could also fit a regular random effects model, treating each
sample as independent. They you could compare the two models with a
likelihood ratio test to determine whether there is dependence between
samples nested within studies (that is, whether the study-level variance
component is positive).


On Thu, Dec 13, 2018 at 8:24 AM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:

> I would suggest to use a multilevel model for this. This is in fact the
> perfect application of the three-level model described by Konstantopoulos
> (2011):
> http://www.metafor-project.org/doku.php/analyses:konstantopoulos2011
> So, in this case, we would add random effects for studies and groups
> within studies.
> Best,
> Wolfgang
> >-----Original Message-----
> >From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-
> >project.org] On Behalf Of Anna-Lena Schubert
> >Sent: Thursday, 13 December, 2018 9:49
> >To: r-sig-meta-analysis using r-project.org
> >Subject: [R-meta] Quick question about multiple independent samples
> >within one study
> >
> >Hi everyone,
> >
> >in my current meta-analysis, I'm looking at a single DV in each study.
> >However, some studies report multiple samples (e.g., children and
> >adults). The samples are utterly independent, but the measures used
> >across samples are equal. Would you suggest that I treat those studies
> >as correlated in a random-effects model or can I treat them as unrelated
> >as the samples are independent of each other?
> >
> >Thanks,
> >
> >Anna-Lena
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