Customer Reviews

Basic & Clinical Biostatistics

5 star:		(6)
4 star:		(6)
3 star:		(2)
2 star:		(0)
1 star:		(8)

 

 

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 :-)

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.

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.

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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.

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.

I actually thought this book was pretty good. I haven't used the cd. The definitions are pretty clear. I use this in conjunction with Gordis' Epidemiology for quick review. I find Rothman and Greenland is not good for that. When I am thinking about research design and elements of statistical analysis this book is easy to turn to to just go over why one test may be better than another--I am a medical student with an MPH in epi who has worked on several research projects, and I think this book is pretty helpful as a simple aid in the transition from research assistant to co-investigator.

I have very little background in biostats, and need to learn it for medical research and research design.

This book is difficult to read, has far too much emphasis on mathematics and far too little empahisis on concept. After a whole quarter in Biostats using this book, I can tell you very little about how and when to employ certain basis statistics tests or interpret them with confidence. The answers in the back are ofter erroneous, as is some of the text (according to my professor).

The only thing I can seay that is good about this test is that the NCSS software that comes with it I think may be helpful at some point.

I am back in the market for a better book!

This book is a great idea at introducing this field but the number of errors are SO BAD that the least the authors could do is maintain a current errata website...The right thing would be to recall the book and fix errors...

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For example: I was reading the chapter on Survival and Figure 9-3 doesn't agree with Table 9-3 (the survival probability values and times when they change). Poor captions in figures.

The book is very detailed and an excellent read and resource for anyone who is in the field of science and someone who reads scientific peer-reviewed journal articles. Though there were some errors in some calculations in the book, overall, it is very helpful and a great way to learn biostatistics and applications in the clinical setting and research settings.

I had to purchase this book for a class I am taking. This is a fourth edition book and I have to correct errors before reading each chapter. I give publishers some leeway on a first edition, but by the fourth the kinks should be worked out. Also, there is some crucial information missing when making the calculations and sometimes it does not give enough detail on how to work through the problems.

A hard plus if your looking for pregrad. introductory clinical biostatistics. However I agree with other reviews that the layout or format could be arranged more powerfully, and the mechanics explained with more and better examples with a little more detail. Some of the examples in the book are excellent. I, especially, liked the Methods for Analyzing Survival. I disliked the explanations on statististical power as well as calculating sample populations necessary (n=?)to obtain clinical significance. This book is a good bone to start knawing on, however, the meat is found in other supplemental texts; therefore, reference footnotes are needed which- nowadays- should include, reference books, journals and webpages.