Reviews of "Statistical Evidence."
This web page will track any published reviews and list any upcoming reviews.
Muche R. GMS Medizinische Informatik, Biometrie und Epidemiologie 3(1): Doc01 (20070315). [Full text] [PDF] This review is in German. I did run through a translation using BabelFish, but there appear to be a lot of idioms that translate poorly (example: "Evidence based Medicine – EBM – is for some time in all mouth"). The reviewer seems to like the picture-rich and humorous language and the many examples from freely accessible sources.
Julian JA. Statistics in Medicine 2007; 26: 3825-2826. doi: 10.1002/sim.2908.
Stephen Simon’s Statistical Evidence in Medical Trials is an enjoyable book that attempts to provide a simple guide for the consumer of the medical research literature. In general, he has accomplished this, but I think a number of important topics have not been covered. For the statistician with little or no experience or training in medical research, this book will be an easy read. For the student of epidemiology, the book is useful as a gentle introduction, and the paperback edition is priced reasonably. Its worth as a reference book, though, is limited.
Karlsson A. Pharmaceutical Statistics 2007 (June); 6(2): 149. doi: 10.1002/pst.278. [Full text] [PDF]
To conclude, although it has some shortcomings, this is a very interesting and useful book, especially for consumers of research with a limited knowledge of statistics, but even for producers of research. The main message is the importance of aspects of statistics other than formulas or calculations, such as selection of the right control group and avoidance of bias, which make the formulas more or less useless according to how they are implemented. Most practical statisticians in the pharmaceutical industry will find this book very useful.
Davis JW. The American Statistician 2007 (May); 61(2): 186
This book is the perfect remedy for those in the medical profession who took a statistics class but came away wondering how all the pieces fit together.
The author does a good job of conveying the lessons in a very understandable manner, peppering the text with stories, analogies, and the occasional joke. I found the book quite enjoyable to read, and sometimes hard to put down, even though I knew "how the story would end." This book is a real gem, and its intended audience will benefit from it immensely.
Martin J. Evidence-Based Medicine 2007; 12: 59; doi:10.1136/ebm.12.2.59. [Full text] [PDF] This review was reprinted in ACP Journal Club. 2007 Jan-Feb; 146: A10.
Clearly this book is not "just another statistics book." Rather, it borders on the side of being revolutional—a statistics book without numbers! While this might be considered near sacrilege in the world of pure statistics, for the purposes of inciting balanced, practical, evidence-based clinical decision making, it is nearly a 5 star resource. The tasteful humour injected throughout the text is just the perfect spoonful of sugar to make the medicine go down.
Dhar SK. Journal of Biopharmaceutical Statistics 2007: 5
The author uses conversational language with a good sense of humor and is able to explain complex concepts using simple stories and amusing anecdotes. This makes the book beneficial, not just for clinical researchers or students, but also as a valuable teaching tool for biostatistics trainers.
Sabin CA. HIV Clinical Trials 2007 (further publication details unknown)
Despite its title, ‘Statistical Evidence in Medical Trials’ (Stephen D Simon, Oxford Statistics) is not a statistics textbook – instead, it aims to provide the reader with a list of the most important questions that should be asked of any research to ensure that the quality of the evidence provided has been thoroughly assessed and that the conclusions are interpreted with appropriate caution. As a result, the book is ideal for those who wish to be able to read and appreciate the broad statistical concepts contained within the medical literature. It is assumed that the reader is familiar with the most common statistical techniques (although a chapter is provided in which some of these are discussed) and readers hoping to learn more about these would be better advised to read a more specialised textbook. However, for those who are familiar with the general principles of statistical analysis, this book provides an additional guide to some of the ‘softer’ issues that are often ignored in statistics texts, most notably a detailed description of bias and clinical relevance. Non-medics will also benefit from reading the book – although the many examples cited are largely medical, they have been chosen so that most reasonably educated readers will understand the concepts and the issues discussed have wider applicability. Indeed, the author suggests that the book may be suitable to journalists and lawyers, as well as to patients who wish to find out more about their own illnesses.
Goldstein R. Technometrics 2007 (February) ; 49(1): 107-108.
Nothwithstanding my negative comments and tone above, there are valuable points here; they are, however, generally too hard to find and some of them are undercut the author's misguided attempt to be "fair." If the author were to clean up the typographical errors and omissions and highlight the main points, the result would be a much better book.
Hamilton C. Baylor University Medical Center Proceedings 2006 (October): 19(4); 419. [Full text] [PDF]
Simon's text does a wonderful job of presenting and explaining the relevance of statistical issues in a manner understandable even to those with no statistical training whatsoever.
Rooney R. International Journal of Epidemiology 2006; 35(5):1368-1369; doi:10.1093/ije/dyl182 [Excerpt]
This book is a clear, concise, and interesting read and should prove to be a useful guide. The examples and case studies make it easy to understand difficult concepts and the jokes and stories make it fun. There are some salient points and hopefully the reader will be enthused about looking at the published research and be more confident about distinguishing between the good and the bad.
Here are the reviews that appear on various websites.
Shah BN, UK Amazon.
Overall, this book is excellent and I would highly recommend it to anyone wishing to learn more about interpreting clinical research.
Farewell VT, Short Book Reviews On-Line.
The book succeeds very well in providing an interesting and informative introduction to the proper assessment of published medical research.
This work is licensed under a Creative Commons Attribution 3.0 United States License. This page was written by Steve Simon and was last modified on 2009-11-04. Need more information? I have a page with general help resources. You can also browse for pages similar to this one at P.Mean: Statistical Evidence in Medical Trials (created 2005-01-27).