[R-meta] Dependencies in data: multiple studies with overlapping sample sizes
Viechtbauer, Wolfgang (SP)
wolfg@ng@viechtb@uer @ending from m@@@trichtuniver@ity@nl
Thu Oct 25 22:08:05 CEST 2018
Indeed, when different groups are contrasted with a common group, then the estimates are no longer independent (due to 'reuse' of the information from the common group). Gleser & Olkin (2009) call this the 'multiple-treatment study' case. Code to compute the covariance between the log odds ratios can be found here:
A model that incorporates these covariances can then be fitted. So, in this scenario, there is no need to use cluster robust methods. Not sure if the latter would be appropriate for this amount of studies, even when using the small sample corrections.
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On Behalf Of Lasse Bang
Sent: Thursday, 25 October, 2018 10:04
To: 'r-sig-meta-analysis using r-project.org'
Subject: [R-meta] Dependencies in data: multiple studies with overlapping sample sizes
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!
Lasse Bang, Ph.D
Regional Department for Eating Disorders (RASP)
Oslo University Hospital, Ullev�l HF
E-mail: Lasse.Bang using ous-hf.no<http://firstname.lastname@example.org> / I.Lasse.Bang using gmail.com<mailto:Lassebang199 using hotmail.com>
Phone: +47 23 02 73 71 /+47 41 42 97 04
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