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I have somewhat extensive experience in meta-analysis, but remain an avid reader on this topic.

I am thus wondering, which is the best book to learn meta-analysis in general?

And which books are the best for selected topics, e.g. diagnostic meta-analysis, individual patient data meta-analysis, Bayesian meta-analysis, and network meta-analysis, just to name a few?

This is not a banal question, as a simple Amazon search returns more than 900 results.

Interestingly, Amazon suggests as most relevant Introduction to Meta-Analysis by Borenstein and Hedges, whilst the first for feedback is The Handbook of Research Synthesis and Meta-Analysis by Cooper and Hedges. Google Books instead lists first Meta-Analysis in Social Research by Glass, McGaw, and Smith, whereas Google Scholar clearly establishes the Cochrane Handbook for Systematic Reviews of Interventions by Higgins and Green as the most quoted one.

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My favorite is: Introduction to Meta-Analysis 1st Edition by Michael Borenstein (Author), Larry V. Hedges (Author), Julian P. T. Higgins (Author), Hannah R. Rothstein (Author). ISBN-13: 978-0470057247

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For theory the classic book by Olkin and Hedges is my favorite. The practical book by Bornstein, Hedges et al. is really a good applied book that introduces and explains their software.

Larry V. Hedges and Ingram Olkin. "Statistical Methods for Meta-Analysis" Academic Press, 2014

Borenstein, Michael, et al. "Introduction to Meta-Analysis". John Wiley & Sons, Ltd, 2009.

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    $\begingroup$ Giving full bibliographic references would enhance this answer. $\endgroup$ – Nick Cox Nov 28 '16 at 9:05

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