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Basic & Clinical Biostatistics: Fourth Edition [Anglais] [Broché]

Beth Dawson , Robert G. Trapp

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Descriptions du produit

Quatrième de couverture

The ideal way to develop sound judgment about data applicable to clinical care.
*First choice of students, educators, and practitioners
*A thorough, meaningful, and interesting presentation of biostatistics
*Helps students become informed users and consumers of biostatistics

" ... Readers may 'learn' and then 'do' immediately ... I learned a lot from this book."
—Online review of the Third Edition

Learn to evaluate and apply statistics in medicine, medical research, and all health-related fields.
*Emphasis on the basics of biostatistics and epidemiology and the clinical applications in evidence-based medicine and decision-making methods
*NEW chapter on survey research
*Expanded discussion of logistic regression, the Cox model, and other multivariate statistical methods
*Key Concepts in each chapter pinpoint essential information
*Presenting Problems drawn from studies in the medical literature that illustrate the various statistical methods
*CD-ROM with NCSS statistical software, procedures, and data sets from the presenting problems
*End-of-chapter exercises
*Multiple-choice final practice exam

Biographie de l'auteur

Beth Dawson, PhD, Southern Illinois University School of Medicine, Springfield, IL

Robert G. Trapp, MD, Springfield, IL

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Dans ce livre (En savoir plus)
Première phrase
The goal of this text is to provide you with the tools and skills you need to be a smart user and consumer of medical statistics. Lire la première page
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Parcourir les pages échantillon
Couverture | Copyright | Table des matières | Extrait | Index
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Commentaires client les plus utiles sur (beta) 3.2 étoiles sur 5  26 commentaires
25 internautes sur 28 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Book Review for the 3rd edition: Just the Facts 21 novembre 2000
Par Ralph Leonard, MD - Publié sur
1. Huge breadth: covers topics of interest to clinicians and plenty of material (see below) for aspiring researchers. Algorithms and lay-out keeps the big picture easily in view. 2. Solved problems: methodical answers, clear, instructive. 3. Appropriate depth: is mathematically correct -- not oversimiplified at the cost of accuracy -- while introducing the key formulas and concepts. Much explanatory text makes the ideas clear rather than esoteric derivations. 4. Includes statistics software: menu-driven so "user friendly," has basic and advanced functions. 5. Practical approach: sample problems and exercises are modelled around cases rather than just theory. These cases have data-base directly on the accompanying software so readers may 'learn' and then 'do' immediately. 6. I learned a lot from this book :-)
12 internautes sur 12 ont trouvé ce commentaire utile 
4.0 étoiles sur 5 Good Primer 17 août 2005
Par Mattelfesso - Publié sur
I bought this book in 1990 (an older version) and have never had a statistics course. I have found it to be an extremely helpful starting point for the application of statistical tests to biomedical problems. From this I have gone on and used more sophisticated tools for computation and have only rarely needed to seek out the advice of experts.

The book is packed full of information and covers the broad range of problems most often encountered in biomedical science. It emphasizes an understanding of the choice an appropriate test for a given problem. Flow charts also help guide the user to the right test and the correct chapter. For this reason I have come back to it repeatedly over the years and it has become well worn. It is sparse on explanation of the statistical or mathematical proofs of methods so it is more of a cookbook than as a theoretical treatise.
6 internautes sur 6 ont trouvé ce commentaire utile 
3.0 étoiles sur 5 Not good for a beginner - useful as a reference 19 août 2008
Par Alec Mclure - Publié sur
Format:Broché|Achat vérifié
This book was used in my grad level intro biostatistics course some months ago- for an intro course (or at least for my learning style) it just didn't work and I had to find alternate resources for almost everything I was studying. (Note that I heard the same or similar from a few of the other students in my class in informal conversation).

I think they were trying to be innovative with how they arranged it - but, at least for me, the material didn't build logically and I kept jumping back and forth trying to figure out what was going on and build my knowledge/expertise in a logical way.

Other people have pointed out the errata, which my teacher had to bring up every once in a while - for a beginner who wouldn't be able to identify them, it's not a good thing.

On a plus, it's nice that it comes w/ some databases on CD you can play with. There are some good flowcharts on picking a test. And it does present good clinical context.

I'll keep the book as an additional reference, but in my opinion it was not the right one to learn the basics on if you're starting at zero. From a student's perspective, wouldn't recommend it at all for a beginning class.


A couple of years later - and a fair amount of biostats under my belt - I think I was right. It's one of my useful references now that I've learned biostats from other sources.
7 internautes sur 8 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Excellent brief review of biostats 6 octobre 1997
Par Un client - Publié sur
This book is the best brief review I've seen on the subject. Good clinical examples make the concepts accessible to medical students and residents, without sacrificing mathematical rigor.
3 internautes sur 3 ont trouvé ce commentaire utile 
3.0 étoiles sur 5 Good, but could be very good 13 mai 2010
Par JoeT - Publié sur
Format:Broché|Achat vérifié
1. Excellent worked examples from real clinical studies.
2. The explanations are very good overall.

1. The software is basically useless for the text. Only a fraction of the examples are usable using the NCSS software provided, and even the datasets provided do not map to the examples in the text (at least, I couldn't get the same results, even when using Stata or R). Besides, there is no explanation on how to use NCSS and NCSS docs are pretty lame.
2. If NCSS was so great, why where there so many outputs from other software packages?
3. Don't ask questions in each of the chapters and not provide answers. I don't mean the problems at the end of the chapters, but the questions asked at various points within each chapter. Asking a question without giving an answer is not good for learning.

1. Rewrite all the code using R. It's a free software package and all the statistics can be done using it.
2. Make sure the datasets map to the what's in the book. Otherwise, how do you know you're calculating it correctly?
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