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Are there any implemented methods in R that could be used to assess publication bias in a meta-analysis of diagnostic accuracy (Egger's test, funnel plots)? One way would be to change sensitivites and specifities to log diagnostic odds ratios (logDOR), run meta-analysis on the logDOR using common rfx-models and then e.g. use funnel() and regtest() from the metafor package. However as I understand the bivariate approach (Reitsma et al., 2005) is to be prefered. But if a run a bivariate linear model, how can I assess publication bias?

library(mada)
data(Dementia)
(fit <- reitsma(Dementia))
summary(fit)
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  • $\begingroup$ I'm not an expert on the topic, but from what I have heard from experts in the field is that these tests don't work for reviews of diagnostic accuracy testing and that new methods are currently being developed. I would suggest you check out the guidance from the Cochrane Collaboration. Will update my post if I find anything conclusive. $\endgroup$ – abousetta Aug 8 '13 at 23:04
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There is an older paper of Deeks et al justifying the use of the diagnostic odds ratio for this purpose:

on this method:

http://www.ncbi.nlm.nih.gov/pubmed/16085191

The work of Deeks et al is not related to the bivariate model. From my limited experience I can nevertheless recommend this approach.

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Check out the Meta-Analysis Task View

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  • $\begingroup$ Could not find anything regarding publication bias in the mentioned packages for diagnostic accuracy: mada, HSROC, metamisc, bamdit... $\endgroup$ – jokel Aug 8 '13 at 11:24

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