Book Description
This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes.
Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way.
The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided. For many students and researchers learning to use these methods, this one book may be all they need to conduct and interpret multipredictor regression analyses.
The authors are on the faculty in the Division of Biostatistics, Department of Epidemiology and Biostatistics, University of California, San Francisco, and are authors or co-authors of more than 200 methodological as well as applied papers in the biological and biomedical sciences. The senior author, Charles E. McCulloch, is head of the Division and author of Generalized Linear Mixed Models (2003), Generalized, Linear, and Mixed Models (2000), and Variance Components (1992).
From the reviews:
"This book provides a unified introduction to the regression methods listed in the title...The methods are well illustrated by data drawn from medical studies...A real strength of this book is the careful discussion of issues common to all of the multipredictor methods covered."
Journal of Biopharmaceutical Statistics, 2005
"This book is not just for biostatisticians. It is, in fact, a very good, and relatively nonmathematical, overview of multipredictor regression models. Although the examples are biologically oriented, they are generally easy to understand and follow...I heartily recommend the book"
Technometrics, February 2006
"Overall, the text provides an overview of regression methods that is particularly strong in its breadth of coverage and emphasis on insight in place of mathematical detail. As intended, this well-unified approach should appeal to students who learn conceptually and verbally."
Journal of the American Statistical Association, March 2006
Customer Reviews:
very good book, compact but comprehensive.......2007-05-12
This book covers a wide range of topics in Biostatistics, in a comprehensive, but not overwhelming way. In my opinion this book has the potential of being useful to a broad audience, from Statisticians to other professionals who do health related research.
Excellent book ..........2007-01-09
A very specific book, with a lot of details for a statistitian
Average customer rating:
- Not for beginners
- More useful than other beginner's texts but...
- The mediumýs viewpoint
- The beginner's viewpoint
- A Great Desk Reference for Biologists
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Biostatistical Analysis (4th Edition)
Jerrold H. Zar
Manufacturer: Prentice Hall
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ASIN: 013081542X |
Book Description
The latest edition of this best-selling biostatistics book is both comprehensive and easy to read.
It provides a broad and practical overview of the statistical analysis methods used by researchers to collect, summarize, analyze, and draw conclusions from biological research data. The Fourth Edition can serve as either an introduction to the discipline for beginning students or a comprehensive procedural reference for today's practitioners.
Customer Reviews:
Not for beginners.......2007-03-16
I own this book, which I purchased for a graduate-level statistics class. This book does include virtually everything you'd need as a biological statistician, but I have found most of it totally unaccessible. It's far too verbose which makes it difficult to plow through and I feel it's mostly obsolete since it makes no reference to computer software. Since statistics is now a field based almost exclusively on computer programs, a book based entirely on doing statistics by hand is not helpful! I'd say, save your $100 and look elsewhere (like the literature and an SPSS manual).
More useful than other beginner's texts but..........2006-07-17
As someone who recently retired from analyzing ecological data after a decade of it, I found this book to be pretty good one-stop shopping. I wouldn't say it's an introduction to stats so much as it is a systematic compilation of all the "traditional" statistical topics (t-tests, regressions, etc). As such, it contained some useful formulas that do not occur in regular "Stats 101" texts, such as sample size estimators for various analyses.
However, there are two things it is missing. As mentioned by other reviewers, there's no coverage (in the edition I have, anyway) of iterative techniques like bootstrapping, Monte Carlo approaches, etc. Those are coming up a lot in everyday statistical work these days.
More important is something missing from nearly EVERY beginning statistics text (and, often, from college education), which is the place of statistical testing in scientific logic. Too many beginners with statistics get stuck on fishing for significant differences in a stale old dataset rather than really thinking about their subject matter. In the absence of context, statistical "significance" can be deceptive and meaningless. One place to start on this subject is with Murphy & Myor's really good book called Statistical Power Analysis. I learned a ton from that book, which is a good companion for nearly any regular stats text. Happy crunching..
The mediumýs viewpoint.......2004-07-22
I had been teacher of Statistic by several years in some universities of Mexico and the Zar book had been a common company in my classroom all the years. Certainly it is not to begginers, but it is very usefull to proffesors. It usually have answer to assess uncommon series data, as non-normal data, or missing data. The book work almost all the time with data series that have normal distributions, and use non-parametric statistical tools to work with other series distributions. There are other books that deal with it best, considering, by example, tests to data with Poisson or binomial distributions (the common in the biological sciences). However, to undergraduate students, and some graduate students, the Zar "normal" approach work fine. Graduate research or doctoral research is done better not with other book in hand but with other statistical approach in mind, and unfortunately there is not only book to do it. Well, in that case, the Zar book help to understand some of the main points to make high statistical analysis.
The beginner's viewpoint.......2004-06-03
Frankly, I am aghast that the publisher calls this book accessible and appropriate for beginners. I purchased it as the required text for an introductory biometry class, and it has contributed very little to my understanding of biostatistical analysis. After chapter 7 (at best), it is simply incomprehensible. The mathematical notation requires far more than a high school algebra background, and the wording is extremely terse. Yes, it does offer real-world examples, and yes, it does offer a large range of statistical tables, and I am sure that it is good reference for people who are already working as statisticians and who have advanced degrees in statistics. However, it is misleading to call Zar a good introductory text - it is completely inappropriate for beginners. It is too concise in a situation where more words would be useful. Sokal and Rohlf 2nd ed. is far better; Fowler et al. also proved helpful.
A Great Desk Reference for Biologists.......2004-02-10
I have found this book more approachable and user friendly than Sokal and Rohlf. Zar is an excellent desk reference, and has solved a number of statistical problems for me. I reccomend it to anybody who regularly uses statistics in a biological context.
Average customer rating:
- Complicated language
- Principles of Biostatistics
- Hope this suggestion helps u decide
- Biostatistics simplified
- Great book - one of few!
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Principles of Biostatistics (with CD-ROM)
Marcello Pagano , and
Kimberlee Gauvreau
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ASIN: 0534229026 |
Book Description
Marcello Pagano and Kimberlee Gauvreau's PRINCIPLES OF BIOSTATISTICS, Second Edition is a concepts-based introduction to statistical procedures that prepares public health, medical, and life sciences students to conduct and evaluate research. With an engaging writing style and helpful graphics, the emphasis is on concepts over formulas or rote memorization. Throughout the book, the authors use practical, interesting examples with real data to bring the material to life.
Customer Reviews:
Complicated language .......2007-09-29
The language in this book is very hard to understand. I took statistics when I was an undergrad and but this book is so hard to understand. The authors tried to show more steps in the math examples maybe try to make it easier for the reader but it just make it MUCH more complicated to follow. Sometimes I have to read my undergrad statistics book in order for me to understand the same thing it says in this book.
Principles of Biostatistics.......2007-09-19
This book does not give step-by-step instructions on how to solve problems. Therefore, I feel it is not a good book. I still feel very lost after reading chapters in this book.
Hope this suggestion helps u decide.......2007-09-09
This is my first time that I purchased online. I got the book within 3 days and it's in a good condition. Cheaper, got a book, and on time...isn't it enough?
Biostatistics simplified.......2007-06-27
Much easier to grasp than another text on the subject that I have experienced, (Biostatistics... A foundation for anlaysis in the Health Sciences; 8th Edition. Wayne W. Daniel). I am an MPH student with limited math background. Had a 4.0 going before my first experience with biostats. A "D" won't cut it in the program I am completing. Found an alternative Biostats course and the required text,(Principles of Biostats;Marcello Pagano), is much, much, easier for me to grasp. The real world examples and simplified methods make for an easier comprehension for those of us who lack a strong mathematic prerequisite.
Great book - one of few!.......2007-03-23
I've read the other reviews, and seems either you love it or hate it. I used this at Harvard School of Public Health on my 3rd time through bio-statistics (college, med school, MPH). Only this time I got it right, and think it was the balance between some non-calculus theory and practical examples in this book. Not understanding probability distributions at all leads to misapplication, and misuse. I have frequently turned to this as "tune-up book" if I've been away too long. The exercised sets are helpful and "realistic"; however, I do understand the problem with text-books and teacher's manuals that give only 1/2 the answers.
Book Description
The randomized control clinical trial has become the gold standard scientific method for the evaluation of pharmaceuticals, biologics, devices, procedures and diagnostic tests. This trial design has been successfully used in both therapeutic and disease prevention trials. It is superior to alternative designs by eliminating several sources of bias which exist in those designs. This role has evolved over the past three decades in a number of disease areas including cardiology, opthalmology, cancer and AIDS. While the specifics of using the randomized control design for a specific intervention and disease may differ, the basic fundamentals still apply in developing the study protocol and operational procedures. These fundamentals still apply in developing the study protocol and operational procedures. These fundamentals include identifying the specific questions to be tested and appropriate outcome measures, determining an adequate sample size, specifying the randomization procedure, detailing the intervention with visit schedules for subject evaluation, establishing an interim data and safety monitoring plan, detailing the final analysis plan and determining the organizational structure. This text is structured to address the fundamentals as the protocol for a clinical trial is being developed. A chapter is devoted to each of the critical areas of a protocol to aid the clinical trial researcher. The fundamentals described in this text are based on sound scientific methodology, statistical principles and years of accumulated experience by the three authors. Collectively, the authors have been active researchers in a broad area of clinical trials including cardiology, cancer, opthalmology, diabetes, osteoporosis, AIDS, women's health and screening tests. In these studies, the authors have served as members of the steering committee responsible for developing the protocol and as members of data and safety monitoring committees. The fundamentals were proposed in the first edition published in 1981 and have not changed substantially in the later editions. However, the number of examples illustrating the fundamentals has greatly expanded base on the collective experience of the authors. This text is intended for the clinical researcher who is interested in designing a clinical trial and developing a protocol. It is also of value to researchers and practitioners who must critically evaluate the literature of published clinical trials and assess the merits of each trial and the implications for the care and treatment of patients. The test uses numerous examples of published clinical trials from a variety of medical disciples to meaningfully illustrate the fundamentals. Technical design issues such as sample size are considered but the technical details have been suppressed as much as possible through the use of graphs and tables. While the technical material has been kept to a minimum, the statistician may still find the principles and fundamentals presented in this text useful both in a consulting and teaching capacity. The text assumes that the readers have only a modest formal statistical background. A basic introductory statistics course is helpful in maximizing the benefit of the text. However, a researcher or practitioner with no statistical background would still find most, if not all the chapters understandable and useful.
Customer Reviews:
Good overview so far.......2007-02-09
This book has, so far, provided a nice overview of the steps associated with clinical trial design and management. The math is pretty basic, but they do think of a lot of softer issues that are important (e.g. adequate parking is essential to participant retention). The references are quite helpful. I have not finished the book, but expect the second half to retain the quality overview that I have seen in the first half.
Detailed introduction.......2005-08-02
Comprehensive book. Requires good understanding of basic statistics and mathematics for some chapters. However without this, it is still a great book for a solid foundation on Clinical Trial design and conduct.
CONCISE MULTIDISCIPLINARY APPROACH.......2003-01-30
The fact that this book was designed for researchers, who are involved in experimental (clinical) trials, makes the basic knowledge of statistics essential.
Using an interactive multidisciplinary approach to investigation, this handbook embraced all aspects clinical and paraclinical survey. It is very easy-to-follow, and divulges its methodology in concise manner. "Fundamentals of Clinical Trials" is one book that will help alleviate the rigorous chores of epidemiologists. However, an advanced or versatile researcher may complain that some of the information in it are too summarized.
Good intro textbook.......2003-01-04
I used this book for a class that I took last semester on clinical trial.
The authors do a good job of giving a good overview of the topics of interest, in particular: sample size calculation, use of DSMBs, trial design, choice of endpoints, randomization and issues in data analysis.
The chapters on sample size estimation and use of safety monitoring boards are quite heavy on the statistics. If you've never had an intro class in statistics, then these chapters may be way over your head.
There are a few topics that the authors didn't cover so well that I thought should have been more prominent: Choice of primary endpoints in FDA trials, general requirements of the FDA and regulatory information in general, the calculations of meta-analyses.
Overall I am quite happy with this book and will keep it on my shelf as a good reference.
A great introduction to clinical trials.......2001-08-17
This book is a very good place to start for those who want to learn about the design and analysis of clinical trials. However there is a heavy emphasis on statistics - a basic knowledge of stats is essential.
Book Description
This classic text takes an applied and computer-oriented approach to its topical coverage. The book is intended for one or two semester courses in biostatistics at the undergraduate or graduate level offered by departments of biostatistics, statistics, mathematics, nursing and other allied health disciplines, and is also used in some departments of forestry and animal husbandry. Nearly all the examples and exercises make use of real data from actual research projects and reports from health sciences literature. Where appropriate, Minitab, SPSS and SAS commands and printouts are included as part of the examples and solutions to exercises.
Customer Reviews:
Helpful but technical.......2006-11-10
This book is extreamly helpful for academic research. It can be somewhat more technical than most people would need.
Not as impressive as I first thought.......2005-09-23
Daniel obviously knows his statistics; but, I wouldnt think that is too helpful for individuals reading or studying from his textbook.
The reasons are numerous, and all these reasons would reduce anyone's chances of solely using this book, or even using it at all.
The textbook is well organized, however Daniel's writing often is pedantic, repetitive (not in the helpful way) and ambiguous at best.
The examples and solutions occassionaly have serious errors in them which affect the overall outcome of the test (A second consideration is that the book is in it's 8th edition!!! therefore such errors are unacceptable for a person such as myself).
An example can be found on page 239 (example 7.3.2). The pooled variance, as calculated by Daniel is approximately off by 100 simply because he didnt give attention to dividing the numerator with the proper pooled D.F of the samples. The chapter ironically was on hypothesis tests, something extremely important to any line of empirically oriented statistics.
In Chapter 8; which is probably the most important chapter in Bistatistics (ANOVAs) he does not mention the relationship between MSW and sample SD. Also, his usage of Summation in formulas often are unnecessarily overcomplicated. Such is not even seen in professional journals.
I did like this textbook regardless of its many shortcomings, its not because I liked the author's style of writing. Its more or less the fact that my lecturer (I assume) used this book heavily in his lectures and so I used it as a supplementary text.
I would suggest, Chap T. Le's Introductory Biostatistics. However he goes too much into nonparametric methods and proportions and doesnt cocentration (to the degree I wanted) on continous data.
More robust and probably cost effect books are :Introductory Statistics for the Life Sciences by Samuels. But the Best book I have ever seen on the subject is "Introductory Biostatistics for the health sciences" By Chernick and Friis. The book is well priced and no portion of this book, I have seen as being useless.
Excellent Text for 2nd Statistics Class.......2004-10-25
I'm taking my first biostatistics class in medical school, but the text I am using in class (Rosner) has lost me. I subsequently borrowed Daniel's book from the library (only because it has 7th editions), and I am glad that I picked it! Daniel is a good writer. The book is well organized and laid out. Important concepts are emphased and explained with minimum mathematics involved. The well thought out examples are worth working through as well for clarification of the applications of important concepts. However, as a beginner in statistics, I was lost in the midst of mathematics on certain concepts (given that I have a relatively strong mathematics background) without really understanding the meaning of some very basic terms, like percentile, confidence intervals.
What I do is to read another reference book that explains the very basic concepts in plain English first before reading this text. I am currently using Munro's Statistical Methods for Health Care Research. While both of them cover the same set of concepts, Daniel gives me the mathematical and more advanced explainations compare to Munro.
Very Good.......2003-12-19
I have used this and other texts by Daniel over the years and I find you can not go wrong with his works. He is a no nonsense author and a very good writer who uses plenty of examples. Get his nonparametric book also.
Solid introductory reference.......2003-01-09
The title is very appropriate - this text provides a solid foundation in biostats. I used it for an intro course in grad school, and working through the text was very worthwhile. Previously cloudy concepts are now more clear, and I have a great reference for future use. More in-depth biostats deserves a consultation with a statistician, not a longer text. I agree with other reviewers that there are occasional mistakes (which need to be fixed - this is not even the first edition), but overall I would still highly recommend it.
Average customer rating:
- Deceptive
- An original approach. An excellent book on the subject.
- Hey, I got an A in Biostats I
- YES! I could speak and ask questions at journal club without looking like a fool.
- Excellent Statistics Book
|
Intuitive Biostatistics
Harvey Motulsky
Manufacturer: Oxford University Press, USA
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Binding: Paperback
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ASIN: 0195086074 |
Book Description
Designed to provide a nonmathematical introduction to biostatistics for medical and health science students, graduate students in the biological sciences, physicians, and researchers, this text explains statistical principles in non-technical language and focuses on explaining the proper scientific interpretation of statistical tests rather than on the mathematical logic of the tests themselves. Intuitive Biostatistics covers all the topics typically found in an introductory statistics text, but with the emphasis on confidence intervals rather than P values, making it easier for students to understand both. Additionally, it introduces a broad range of topics left out of most other introductory texts but used frequently in biomedical publications, including survival curves. multiple comparisons, sensitivity and specificity of lab tests, Bayesian thinking, lod scores, and logistic, proportional hazards and nonlinear regression. By emphasizing interpretation rather than calculation, this text provides a clear and virtually painless introduction to statistical principles for those students who will need to use statistics constantly in their work. In addition, its practical approach enables readers to understand the statistical results published in biological and medical journals.
Customer Reviews:
Deceptive.......2007-08-10
If you think you can learn Statistics intuitively and without mathematics or in otherwords the easy way, I have an intuitive Brain Surgery book for sale.
An original approach. An excellent book on the subject........2007-06-13
The majority of reviewers really liked this book. I can see why, I did too. The author uses a unique approach to teaching statistics that is focused on calculating and explaining Confidence Intervals (the minimum and maximum value you expect an outcome to be given a confidence level typically 95%) rather than P values (probability outcome is due to chance). He also uses common sense and clearly distinguishes between what is statistically significant and what is "significant." Thus, he translates well statistical mumbo jumbo into plain English. He tells you what you should care about and look for.
He shares with you all the statistical flaws that clinical studies may have including testing multiple hypothesis to come up with just a single statistically meaningful one, using large samples to prove something trivial, using small samples that raises uncertainty level, etc...
His section on Bayesian Logic is excellent. His table on what test or methodology to use given the shape of the data and objective you have is worth the price of the book alone. That's one of the clearest taxonomy of statistical methods I have seen anywhere.
Some knowledgeable reviewers have picked up a few errors the author made. I stumbled upon a couple while attempting to replicate the calculation of a few examples. I emailed the author and each time within an hour he either clarified the calculation or corrected the typo that was present in the book. Given his prompt answers, I can't ding him for the couple of typos I caught.
Although the author presents this book as an introductory one, I recommend the reader acquires a good foundation in basic statistics before studying this book. Forgotten Statistics would fit that bill. Indeed, `Intuitive Biostatistics' covers a huge amount of ground. It is far more than an introductory text. It covers material that is pretty advanced including nonparametric hypothesis tests, non linear regression, logistic regression, Bayesian analysis, etc... If it is the first time you come across that stuff you'd be well served having a solid stats foundation. Given that, this book has a lot to offer. I'll keep it as a great reference for years.
Hey, I got an A in Biostats I.......2007-01-04
I am not a high faltuin' math person, the calculus I went through in undergrad was a struggle and I remember very little. I am a chemist by training, currently seeking my PhD in Public Health while working full time. What that came down to was little to no time to doof around with a muddled textbook or an equally muddled professor or a non-English speaking Teacher's Assistant.
I have no intention of becoming a biostatistician or an epidemiologist, I am interested in policy.
So coming from that perspective, as a student, this book was an absolute God-send.
Not only did I get an A in the class, but I feel like I have a sturdy foundation for my future coursework and career. I will not be intimidated by numbers or jargon because Dr. Motulsky made it all as straightforward and clear as possible, and I recall even laughing a few times.
Overall, if you are in school, facing a biostatics class with extreme trepidation, buy this book as a supplement. Look up the topics in the index as you go and you will have more than the $40 worth of "eureka" moments.
YES! I could speak and ask questions at journal club without looking like a fool........2006-09-25
Helped me from looking a fool during residency. Thank you Harvey!
Excellent Statistics Book.......2006-03-13
Intuitive Biostatistics takes a confidence interval approach that should be required reading for all persons interested in statistics. His discussion of basic statistical concepts in the context of interpreting lab test results is clear and informative and introduces the reader to Bayesian concepts that are presented very simply.
Book Description
Meta-analysis, decision analysis, and cost-effectiveness analysis are the cornerstones of evidence-based medicine. These related quantitative methods have become essential tools in the formulation of clinical and public policy based on the synthesis of evidence. All three methods are taught with increasing frequency in medical schools and schools of public health and in health policy courses at the undergraduate and graduate level. This book is a lucid introduction, and will serve the needs of students taking introductory courses that cover these topics. It will also be useful to clinicians and policymakers who need to understand the quantitative underpinnings of the methods in order to best apply the information that derives from them. The second edition of this popular book adds new material on cumulative meta-analysis as a method to explore heterogeneity. The coverage of cost-effectiveness analysis has been brought into close alignment with recommendations of the U.S. Public Health Panel on Cost-Effectiveness Analysis in Health and Medicine. Many of the examples have been replaced with more current examples, and all of the material has been updated to reflect recent advances in the methods and the emergence of consensus about some previously controversial issues. analysis. These three closely related methods have become even more important for synthesizing research since the first edition was published in 1994. And they have gained legitimacy as tools for guiding health policy.
Customer Reviews:
Best guide for analysis.......2006-12-20
There are several ways to do analysis of the health care industry but this book covers the big three. Cost Effectiveness is the most useful from a business standpoint. This book covers the math and theory behind each of these methods and gives strong arguments for how to write in each of them. As a health and pharmaceutical economist I found this book to be invaluable. It is written very clearly and helps sort through many of the issues especially meta analysis. If you are starting out in the health analyst field this is a must read and a book you will want to have handy at all times.
An excellent introductory text.......2002-02-05
Meta-analysis, as both an applied and theoretical science, continues to develop from its rather humble beginnings. Since most physicians lack a strong background in quantitative science, rigorous statistical approaches to clinical decision making have been slow to gain widespread support. Despite its limitations, meta-analysis is proving to be an important vehicle for making sense of the increasingly overwhelming amount of published data in the biomedical sciences. Petitti's book goes a long way in demystifying meta-analysis for the rank and file and also serves as an excellent introduction to the field for the more statistically literate.
Most of my own work is in meta-analysis and I bought the book exclusively for this content and not information on decision analysis and cost-effectiveness analysis. I do not mean to minimize the importance of the latter but rather point out my own narrow interest in the Petitti text.
The book is well written and concise. Petitti "cuts to the chase" explaining the theory underlying meta-analytic methods and provides many useful examples from the medical literature. The text is easy to follow, understandable and well balanced. A thorough reading should leave the reader well prepared for further exploration of applied meta-analysis as well as capable of articulating its strengths, weaknesses and future direction.
Overall, Petitti's text is an excellent place to start for those interested in learning the fundamentals of "research synthesis". The book is also an extremely handy references for the more experienced practitioner. I highly recommend it.
clearest yet description this topic.......1997-07-08
In a forest of mirky and arcane descriptions of a field that has come to dominate medical research and policy making, this book stands out for its clarity. Dr. Petitti speaks a language that normal people can understand. She avoids jargon and frequently uses quantitative examples that make it easy to plug in your own problems and directly apply her lessons to your tasks. This is easily the best book in print on this topic
Book Description
A comprehensive user-friendly introduction to biostatistics and epidemiology applied to medicine, clinical practice, and research. Features “Presenting Problems” (case studies) drawn from studies published in the medical literature, end-of-chapter, and a CD-ROM with data sets and statistical software programs.
Customer Reviews:
Try another book.......2007-09-01
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.
Basic and Clincial Biostats, Scientific Perspective.......2007-06-28
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.
definitely not helpful for 'basic' or introductory level.......2007-04-08
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!
Good Primer.......2005-08-18
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.
Pretty Good.......2004-08-19
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.
Book Description
- Includes a new chapter on logistic regression.
- Discusses the design and analysis of random trials.
- Explores the latest applications of sample size tables.
- Contains a new section on binomial distribution.
Download Description
* Includes a new chapter on logistic regression.
* Discusses the design and analysis of random trials.
* Explores the latest applications of sample size tables.
* Contains a new section on binomial distribution.
Customer Reviews:
Very good book.......2007-03-12
This book is an excellent alternative to Agresti's "Categorical Data Analysis" for the analyzing of categorical data. The book is comprehensive and less mathematically demanding than Agresti. The book does a tremendous amount with contingency tables and epidemiologic types of data and has many good worked out examples.
There are a couple of features that could be improved in the next edition:
1) Give the statistical tests that are presented names.
Often statisitical procedures/tests are given and they are not given an explicit name. I think that this is an intentional practise of the authors, but I found it very confusing. For instance, there are many chi-square tests out there, each of which can be written in different ways. Why not call them "Pearson's chi-square", "Cochrane's chi-square", etc... so that the reader knows what the authors are talking about?
2) Not enough time devoted to the subject of combining simple proportions (i.e. not fourfold tables) from several samples/studies. Only one method is shown when several others exist.
3) ALL the common methods used to transform proportions should be presented and explained. For instance, the arcsine transformation is left for an exercise.
4) The writing was a bit terse and cryptic at times. I wish the authors had opted for a simpler English sentence structure and aimed to write at as low a level as practically possible. This encourages understanding of the topic rather than the development of eloquent prose.
5) The references were good but the way they were cited was not. In line author names is an outdated reference method that bogs down sentences and clutters pages with useless text. Simple numeric citation markers would have been better.
6) Bayesian methods are developed, but not a much as I might otherwise have hoped.
Average customer rating:
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Biostatistical Genetics and Genetic Epidemiology
Manufacturer: Wiley
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Binding: Hardcover
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ASIN: 0471486310 |
Book Description
Human Genetics concerns the study of genetic forces in man. By studying our genetic make-up we are able to understand more about our heritage and evolution. Some of the original, and most significant research in genetics centred around the study of the genetics of complex diseases - genetic epidemiology.
This is the third in a highly successful series of books based on articles from the Encyclopedia of Biostatistics. This volume will be a timely and comprehensive reference, for a subject that has seen a recent explosion of interest following the completion of the first draft of the Human Genome Mapping Project. The editors have updated the articles from the Human Genetics section of the EoB, have adpated other articles to give them a genetic feel, and have included a number of newly commissioned articles to ensure the work is comprehensive and provides a self-contained reference.
Books:
- Reincarnation and Biology: A Contribution to the Etiology of Birthmarks and Birth Defects Volume 1: Birthmarks
- Research Methods in Physical Activity
- Science as a Process: An Evolutionary Account of the Social and Conceptual Development of Science (Science and Its Conceptual Foundations series)
- Seven Things That Steal Your Joy: Overcoming the Obstacles to Your Happiness (Meyer, Joyce)
- Short Protocols in Molecular Biology (2 volume set)
- Small Fuel Cells, 7th Edition: For Portable Applications
- Systems Bioinformatics: An Engineering Case-Based Approach
- The Allergy Self-Help Cookbook: Over 350 Natural Foods Recipes, Free of All Common Food Allergens: wheat-free, milk-free, egg-free, corn-free, sugar-free, yeast-free
- The Closing of the American Mind
- The Evolutionary Ecology of Ant-Plant Mutualisms (Cambridge Studies in Ecology)
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