[R-meta] Publication bias with multivariate meta analysis
Viechtbauer, Wolfgang (SP)
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Mon Aug 30 11:43:53 CEST 2021
That's one of the main uses of a funnel plot: To see if it looks (roughly) symmetric or not. If it is not symmetric, then in essence this implies that there is a relationship between the estimates and whatever you put on the y-axis of the plot (typically the SEs).
There are many possible reasons for why such a relationship could exist (i.e., why the plot is not symmetric). Publication bias is one of them. For certain effect size measures, there is also an inherent relationship between the observed effects and their sampling variances (and hence SEs), so in this case the funnel plot (and methods based on it) that put the SE (or some function thereof on the y-axis) are inherently flawed. To give one example:
Pustejovsky, J. E., & Rodgers, M. A. (2019). Testing for funnel plot asymmetry of standardized mean differences. Research Synthesis Methods, 10(1), 57-71. https://doi.org/10.1002/jrsm.1332
Unaccounted for moderators that are related to the size of the estimates *and their SEs* could also create asymmetry.
In principle, one could also reason that asymmetry is to be expected if study authors are doing sample size calculations / power analyses before conducting their studies.
I just saw that Gerta also replied and provided a useful reference.
>From: Norman DAURELLE [mailto:norman.daurelle using agroparistech.fr]
>Sent: Monday, 30 August, 2021 10:23
>To: Viechtbauer, Wolfgang (SP)
>Cc: Huang Wu; r-sig-meta-analysis
>Subject: Re: [R-meta] Publication bias with multivariate meta analysis
>Dear list members, dear Huang and Wolfgang,
>thank you for explaining that there is no method for testing for publication bias,
>or more accurately, for explaining that a relationship between observed effects
>and their standard errors does not necessarily indicate publication bias (meaning
>that there are other reasons why one could encounter such a relationship).
>Outside of Huang's question : does funnel plot asymetry necessarily indicate a
>relationship between observed effects and their standard error ?
>I am going to have a deeper read at https://www.metafor-project.org/ but I would
>be grateful for an answer.
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