Product Description
(BMJ Books) Univ. of Bristol, UK. Introduction to the rationale and principles of systematic reviews and an overview of more advanced topics, such as the investigation of bias or the review of prognostic and diagnostic studies. Covers the statistical methods used for meta-analysis. For researchers and healthcare providers.

CUSTOMER REVIEWS (Average Customer Rating: 4.5 based on 2 reviews)

Classic definitive textbook in meta-analysis! by E. Ding

5 Stars
March 21, 2007
This classic book by the legendary experts in meta-analysis and systematic review, Mattias Egger, George Davey Smith, and Doug Altman, is considered the most pre-eminent and most definitive textbook in this area. No other books can compare! Very easy to read with clear explanations, this is the most trusty reference textbook to own when doing systematic reviews and meta-analyses.

Excellent text that is easy to understand by Brant Inman (Somewhere out there)

4 Stars
March 11, 2007
This book is written to be understood and used. Everything is easily accessible, even for the relatively innumerate, and presented in clear, easy English. The authors are to be congratulated on excellent pedagogical prose. The major downside was a skinny statistical section that lacked depth (what was present was VERY clear however). Since the majority of the book is low-level, big-picture explanations of the principles of meta-analysis, I think that an expanded statistical section would not detract. In fact, because the rest of the book is so well explained, I suspect that most readers would have a good appetite for implementing the ideas presented. Those not inclined to read more details on implementation could just skip this section. In particular, I wished the authors had discussed how to combine simple proportions and rates across studies. This is arguably the simplest form of meta-analysis and the one for which nearly no advice exists to guide practise! There are tons of ways to transform and combine rates/proportions and these should have been developed, compared and constrasted for different scenarios. Similarly, I wish that even more Bayesian methods would be presented. Lastly, the software section is old. New ideas using R, Revman, Bugs and other FREE software should be encouraged. Software that costs big dollars is probably not the best thing to present in an international book. Everyone should be able to reproduce the results at their home. Free software ensures this.

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