[R-meta] Dependencies in data: multiple studies with overlapping sample sizes
ruecker @ending from imbi@uni-freiburg@de
Thu Oct 25 11:10:41 CEST 2018
What about a network meta-analysis? More general, methods for adjusting
for common control groups (includin some R code) are found in Rücker G,
Cates CJ, Schwarzer G. Methods for including information from multi-arm
trials in pairwise meta-analysis. Res Synth Methods. 2017
Dec;8(4):392-403. doi: 10.1002/jrsm.1259 PMID:28759708.
Am 25.10.2018 um 10:04 schrieb Lasse Bang:
> Dear experts,
> After comments from reviewers, we are considering performing meta-analyses based on a systematic search which included studies measuring the association between bullying (exposure) and eating disorders (outcome). All studies are case-control studies, and the effect sizes are odds-ratios.
> Based on the included studies, there are three possible meta-analyses which can be performed, based on the type of bullying the participants experienced (generic teasing, generic bullying, appearance-related teasing; each study typically explored more than one type of bullying and so report multiple effect sizes). If performed, these meta-analyses would be based on a small number of studies (k = 6, 7, and 11).
> One of the concerns I have, is that three of the studies have identical healthy control samples. Study A compared patients with anorexia nervosa to healthy controls, study B compared patients with bulimia nervosa to healthy controls, and study C compared patients with binge-eating disorder to healthy controls. The cases are different in each study (n = 52-102), but the healthy controls are the same (n = 204). There is thus an extent of dependency between data from these studies. These three studies are also among the studies with largest total n, and all three studies report all three types of bullying mentioned earlier (so if performing three separate meta-analyses, all three studies would be included in each of the three meta-analyses).
> I'm wondering how to potentially handle this in a meta-analysis? I know such dependencies can be handled using robust variance estimators (robumeta package), but will this work with the amount of studies I am dealing with (k = 6-11)? I know there is a small sample correction available when conducting a meta-regression model in robumeta, but I'm wondering if this is really feasible for the amount of studies that I have.
> All input appreciated!
> Kind regards,
> -Lasse Bang
> Lasse Bang, Ph.D
> Postdoctoral Researcher
> Regional Department for Eating Disorders (RASP)
> Oslo University Hospital, Ullev�l HF
> Oslo, Norway
> E-mail: Lasse.Bang using ous-hf.no<http://firstname.lastname@example.org> / I.Lasse.Bang using gmail.com<mailto:Lassebang199 using hotmail.com>
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Dr. rer. nat. Gerta Rücker, Dipl.-Math.
Institute of Medical Biometry and Statistics,
Faculty of Medicine and Medical Center - University of Freiburg
Stefan-Meier-Str. 26, D-79104 Freiburg, Germany
Mail: ruecker using imbi.uni-freiburg.de
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