Dear Markus
This is not a direct answer to your question, I will leave that to
Wolfgang but two thoughts:
1 - if all the studies have very sparse data
@article{bradburn07,
author = {Bradburn, M J and Deeks, J J and Berlin, J A and Localio,
A R},
title = {Much ado about nothing: a comparison of the performance of
meta--analytical methods with rare events},
journal = {Statistics in Medicine},
year = {2007},
volume = {26},
pages = {53--77},
keywords = {meta-analysis, fixed effects, random effects}
}
suggests, surprisingly, that just collapsing the tables may be adequate
2 - there is a CRAN package mmeta which uses beta-binomial in a Bayesian
perspective. I did not find the documentation very explicit but there is
a paper in JSS.
On 26/11/2015 13:39, Markus Kösters wrote:
Dear all,
I am currently writing a protocol for a meta-analysis which will analyze
suicidal events. Recently, O. Kuss has (DOI 10.1002/sim.6383) published a
paper that suggest using beta-binomial regression methods to incorporate
double-zero studies. He states that �Methods that ignore information from
double-zero studies or use continuity corrections should no longer be used.�
It seems obvious to me that excluding studies with zero events will bias the
results and I am willing to follow his advice. However, I am not a a
biometrician, I have to admit that I am at a loss if and how it is possible
to fit such model within the metafor package. Can someone help me or should
I use the Yusuf�Peto odds ratio method as suggested in the Cochrane
handbook?
Many thanks in advance,
Markus
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