[R-meta] Publication bias/sensitivity analysis in multivariate meta-analysis

Hi all, I read this thread, and the topic interests me, but I didn't quite understand your answer :when you say " Publication bias is a subset of small study effects where you know the 
aetiology of the small study effects. If you do not then it is safer to 
refer to small study effects. "
I don't really understand what you mean.I thought publication bias meant that the studies included in a sample of study didn't really account for the whole range of possible effect sizes (with their associated standard error).Is that not what publication bias refers to ? And if it is, how does it also correspond to the definition you gave ?Thank you !Norman.
----- Mail d'origine -----
De: Michael Dewey <lists at dewey.myzen.co.uk>
?: Huang Wu <huang.wu at wmich.edu>, r-sig-meta-analysis at r-project.org
Envoy?: Sun, 14 Jun 2020 12:54:30 +0200 (CEST)
Objet: Re: [R-meta] Publication bias/sensitivity analysis in multivariate meta-analysis

Dear Huang

Comments in-line

Hi all,

Greetings. I have some questions about publication bias/sensitivity analysis. First, are publication bias and sensivity analysis the same thing? If not, how are they different?

Publication bias is a subset of small study effects where you know the 
aetiology of the small study effects. If you do not then it is safer to 
refer to small study effects. A sensitivity analysis could be almost 
anything but usually it manes fitting the model to one or more data-sets 
similar to the original one. Examples are leave-one-out analysis, or 
using only a subset of supposed higher quality studies.

Second, I saw people use funnel plot, fail-safe N, Egger?s regression test to test publication bias (http://www.metafor-project.org/doku.php/features), are these methods applicable to multivariate meta-analysis? 

Yes they are.

Thanks.

Third, what do you recommend to do publication bias/sensivity analysis in multivariate meta-analysis? Thanks

I think what analysis you do will depend on the scientific question.

Michael

Best wishes
Huang

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