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Using and Understanding Medical Statistics [Englisch] [Gebundene Ausgabe]

David E Matthews , Vernon T Farewell


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Using and Understanding Medical Statistics Using and Understanding Medical Statistics
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For all medical researchers, regardless of their choice between the alternatives tu wurk alune ur with a statisOöan, this book provides the reasons why and occasinns on which to use statistical methods.'Croatian Medical JournalSince the last edition ofthis book was published major developments in computer technology have affected both the practice of medicine and the methods of ana lyzing medical data. These advances make the focus of this revised edition - understanding rnany ofthe statistical methods that are used in modern medical studies- all the more important. Two new chapters have been added by the authors. One provides readers with an introduction tu the analysis of longitudinal data. The other augments previous material concerning the design ofclinical trials, exploring topics such as the use of surrogate markers, multiple outcomes, equivalence trials, and the planning of efficacytoxicity studies. In addition tu providing new information and finetuning the rest of the book, the authors have reorganized the final sis chapters so that the tupics build, naturally, on each other. This latest edition is highly recommended both as an excellent introduction tu medical statistics and as a valuable tool in explaming the more complex statistical methods and techniques used today.

Synopsis

Since the last edition of this book was published, major developments in computer technology have affected both the practice of medicine and the methods of analyzing medical data. These advances make the focus on this revised edition - understanding many of the statistical methods that are used in modern medical studies - all the more important. Two new chapters have been added by the authors. One provides readers with an introduction to the analysis of longitudinal data. The other augments previous material concerning the design of clinical trials, exploring topics such as the use of surrogate markers, multiple outcomes, equivalence trials and the planning of efficacy-toxicity studies. In addition to providing new information and fine-tuning the rest of the book, the authors have reorganized the final six chapters so that the topics build, naturally, on each other. This latest edition is recommended both as an introduction to medical statistics and as a valuable tool in explaining the more complex statistical methods and techniques used today.

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11 von 11 Kunden fanden die folgende Rezension hilfreich
The language and principles of biostatistics made accessible 16. Februar 2001
Von Robert E. Hurst - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
For what this book intends, it truly is outstanding. In general, the medical researcher of any kind is at a severe disadvantage in dealing with professional biostatisticians because often the two do not speak a common language. This very readable, interesting and clearly written book gives the scientist enough knowledge to deal with most relatively simple cases in a language that we understand. With the basic principles of medical statistics made comprehensible, we are able to understand many of the simpler software packages well enough to perform basic statistical analyses and, more importantly, are able to converse intelligently with biostatistical professionals and to design studies that will pass muster. Unlike another reviewer, I do not feel that not covering SAS or other software programs is a disadvantage. No book can cover everything, and this book covers the basics and intermediate levels far better than any book I have seen, certainly better than any biostatistics book written by biostatisticians intended for other biostatisticians. This book understands that biostatistics is a tool, not a fundamental discipline, for the vast majority of scientists and is written to them. The book serves as a ready reference and review if one does not perform these analyses on a daily basis. This book should be on the shelf of every life scientist.
7 von 8 Kunden fanden die folgende Rezension hilfreich
Intermediate Level Medical Statistics 17. Juli 2000
Von Daniel Albert - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
Want to get beyond primers and introductory texts but lack the background and expertise for the advanced texts. Here is a truly intermediate text which covers a broad range of topics and permits the reader to advance to the next level. This book is chock full of insights without getting mired down in technical detail and nomenclature. It delves just deep enough to give the arguments a foundation and extends them up to the point of clarity without undue complexity. It can be read by anyone with a basic understanding and is a good text for epidemiologically oriented medical scientists. I wish that it was paired with an advanced text that explored each one of the topics in more depth since many of the techniques are not described in enough detail to perform the analysis without refering to other source material. Some greater attention could also be given to the well established statistical software packages such as SAS, SPSS, and STATA. It does repeatedly make the valuable point that if you proceed through an analysis without professional biostatistical consultation you are likely to be short changing your study or even commiting errors. Take heed. It is important to know enough biostatistics to understand the techniques but in almost all cases it is better to work with a professional biostatician than to go it alone. I only wish that there were more medically savvy biostaticians like Matthews and Farewell.
2 von 2 Kunden fanden die folgende Rezension hilfreich
The "Gold Standard" 30. November 2009
Von Prime buyer - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe|Von Amazon bestätigter Kauf
I have had the first edition of this book for decades. It has been a trusty reference for me, a practicing clinician with a need for statistics for clinical research. This "bible" gives a clearly understandable overview of common statistical approaches to clinical problems. It has proven an invaluable adjunct to computerized statistical packages: the book tells me the "why" in selecting a statistical method, while the software will do the "how." Without the book, it would be too easy to perform calculations that are inappropriate or have no relevance to the problem at hand.

This new addition is a welcome update, with new sections on ROC analysis and other topics.

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