Book Description
The definitive reference work on clinical trials, this book presents a wealth of detailed, practical information on the design, conduct, and analysis of both single center and multicenter trials.No other book on clinical trials offers as much detail as Meinert does on such issues as sample size calculation, stratification and randomization, data systems design, consent form development, publication policies, preparation of funding requests, and reporting procedures. ... Read more

Customer Reviews (1)

clinital trials
A good book on clinical trials of the first ste ... Read more

Book Description
Continuing advances in biomedical research and statistical methods call for a constant stream of updated, cohesive accounts of new developments so that the methodologies can be properly implemented in the biomedical field. Responding to this need, Computational Methods in Biomedical Research explores important current and emerging computational statistical methods that are used in biomedical research.
Written by active researchers in the field, this authoritative collection covers a wide range of topics. It introduces each topic at a basic level, before moving on to more advanced discussions of applications. The book begins with microarray data analysis, machine learning techniques, and mass spectrometry-based protein profiling. It then uses state space models to predict US cancer mortality rates and provides an overview of the application of multistate models in analyzing multiple failure times. The book also describes various Bayesian techniques, the sequential monitoring of randomization tests, mixed-effects models, and the classification rules for repeated measures data. The volume concludes with estimation methods for analyzing longitudinal data.
Supplying the knowledge necessary to perform sophisticated statistical analyses, this reference is a must-have for anyone involved in advanced biomedical and pharmaceutical research. It will help in the quest to identify potential new drugs for the treatment of a variety of diseases. ... Read more

Book Description
This is a practical introduction to multilevel analysis suitable for all those doing research. Most books on multilevel analysis are written by statisticians; those books are difficult for non-mathematical researchers. In contrast, this volume provides an accessible account on the practical application of multilevel analysis in research. Many worked examples, with computer output, are given to illustrate and explain this subject. Datasets of the examples are available on the internet, so the reader can reanalyze the data. This approach will help bridge the conceptual and communication gap that exists between researchers and statisticians. ... Read more

Customer Reviews (3)

Enough for you to get acquainted with these models
The book is easy to understand and presents a series of situations where multilevel models are applied, in the context of epidemiological analysis. The examples are mostly very simple, and I don't think the book will help if you want to fit models. If you want to understand them better, then it may be of use. I have some other restrictions as well - some concepts presented in chapter 2 (section 2.8.1) are in direct contradiction with MLwiN user's guide (version 2, 2005, section 7.5, p.86). My understanding is that the latter is correct. Also, a model fitted in chapter 3 with a dichotomous variable random at level 2 includes the covariance parameter, what looks wrong to me. All in all, I think there are better options for an introductory text, e. g. Snijders & Bosker (1999).

A Practical Guide
A good introduction to multilevel analysis that addresses the practical issues that confront researchers.

A friendly guilde to multilevel analysis
Twisk's work is very good for those who are not experts in mathematics and would like to apply this statistic method for investigating cluster effect.Through the tutorial journey mainly illustrated by MLwiN, readers can easily catch the general picture of multilevel analysis and make sense of interpretation and application.The comparison of different statistic software used in multilevel analysis and the concise text for power analysis were another two precious gifts the author gave us. ... Read more

Book Description
Focusing on applications to research, clinical trials, and quality control, Basic Statistics & Pharmaceutical Statistical Applications is a practical, easy-to-use text and reference that builds a basic knowledge of statistics. Accessible and non-threatening, it discusses all of the commonly used statistical tests and presents them with examples and worked out results. The emphasis is on correctly interpreting research results rather than on theory. Thoroughly revised and expanded, this edition includes new chapters on measures of associations, odds and relative risks ratios, and survival statistics. Other new material addresses process capability, tolerance limits, and repeatability/reproducibility. ... Read more

Book Description

Basic Biostatistics presents a multidisciplinary survey of biostatics methods, each illustrated with hands-on examples. Methods range from the elementary, including descriptive statistics, study design, statistical interference, categorical variables, evaluation of diagnostic tests, comparison of means, linear regression, and logistic regression. These introductory methods create a portfolio of biostatistical techniques for both novice and expert researchers. More complicated statistical methods are introduced as well, including those requiring either collaboration with a biostatistician or the use of a statistical package. Specific topics of interest include microarray analysis, missing data techniques, power and sample size, statistical methods in genetics. Expert advice is given on when to seek statistical help, and how to conduct a meeting with the statistical collaborator or consultant. Basic Biostatistics is an essential resource for researchers at every level of their career.

Book Description
Although adaptive design methods are flexible and useful in clinical research, little or no regulatory guidelines are available. One of the first books on the topic, Adaptive Design Methods in Clinical Trials presents the principles and methodologies in adaptive design and analysis that pertain to adaptations made to trial or statistical procedures that are based on accrued data of ongoing clinical trials. The book also offers a well-balanced summary of current regulatory perspectives and recently developed statistical methods in this area.After an introduction to basic concepts and statistical considerations of adaptive design methods, the book questions the impact on target patient populations as the result of protocol amendments and discusses the generalization of statistical inference. The authors also present various adaptive design methods, including where hypotheses are modified during the conduct of clinical trials, for dose selection, and commonly used adaptive group sequential design methods in clinical trials. Following a discussion of blind procedures for sample size re-estimation, the book describes statistical tests for seamless phase II/III adaptive designs and statistical inference for switching adaptively from one treatment to another. The book concludes with computer simulations and various case studies of clinical trials.By providing theoretical and computer simulation results, method comparisons, and practical guidelines for choosing an optimal design, Adaptive Design Methods in Clinical Trials fills the need for a unified, comprehensive, and updated resource in the clinical research and development of adaptive design and analysis. ... Read more

Customer Reviews (2)

This book is a "beta" version
This book's best features are its bibliography (about 240 entries) and its broad survey and taxonomy of adaptive methods. Its publication represents an important step in popularizing adaptive trials and, thus, streamlining drug/device/biologic development pipelines.

The book is, however, filled with inaccuracies on several levels: incorrect grammar and equation references, undefined symbols, a reference to a non-existent appendix, unclear language (e.g., what is the "statistical strength for rejecting Ho" on Page 150?), mathematical typos [e.g., P(x|y,theta) rather than P(y|theta) in the integrand for the posterior predictive probability distribution P(y|x)], and misapplications of statistical philosophy (e.g., using Neyman-Pearson hypothesis testing for statistical inference, identifying the p-value as a post-hoc type I error rate). In the sample I took of about 1/3 of the pages, about 120 errors occur. The book should be considered only a pre-publication "beta" version. Any second edition should receive much more attention to detail.

A statistician or clinical scientist planning a potentially adaptive trial could use this book to learn about some of the aspects of a trial that can be made adaptive. The book could also help him/her to assess the assumptions and mathematical complexity of methods under consideration. However, when it comes to actually performing an analysis, one would want to use the bibliography to obtain the relevant articles and books, perhaps together with Chang's "Adaptive Design Theory and Implementation Using SAS and R" (Chapman & Hall/CRC Biostatistics).

Overall, this book disappointed me. The authors should have had several more collaborators and copyeditors check their work.

Great contribution to pharmaceutical industry
I meet the second author, Mark Chang, at a conference on adaptive designs. I work as a professional statistician in the pharmaceutical industry.For the past several years, at least ten, these ideas have been the topic of research and it is being investigated as a possible way to speed up drug development and its development is being encouraged by the FDA.There has not been a formal statistical text covering the existing theory and its application to clinical trials.Consequently, when we knew this was coming out we preordered it and have been studying it since it came out last November.

The book has lived up to expectations.Adaptive designs are very similar to group sequential designs in that they have planned times to make preliminary assessment of the trial data and then decide whether or not to continue the trial or modify the design.Adaptive designs can be more flexible than their group sequential counterparts.They even can allow changes to the protocol as long as the criteria for making such changes are mapped out in advance of the trial.

These methods have been controversial in the past and simulation studies are often required to determine their properties.But there has been enough development now that some designs are being applied in real trials.In fact we are considering a two stage adaptive design similar to the ones described in this text (except applied to bioequivalence).

Later this year Mark Chang is coming out with an applied text that include SAS macros to aid in the implementation of the methods.A preview of the manuscript was displayed at an adaptive trials conference that I attended recently.I can enthusiastically recommend that one even more than this one!However, any biostatistician working on clinical trials should have this book on his or her bookshelf. ... Read more

Book Description
This text is an easy-to-understand, application-oriented guidebookfor learning the basic principles of epidemiologic investigation. Numerousopportunities are presented to apply and test learning through problems andapplication exercises. Answers are provided. ... Read more

Customer Reviews (1)

Excellent For USMLE
I took my USMLE in 1997, I found this review extremel helpfull, I did not have any problemes answering questions in USMLE, which I owe to the great presentation of Info, easy to remember the well organized materials, tables, figures.Now I am a resident, I easily remember the pages, tabletes. I frequently used before journal clubs. I recomended for every USMLE taker. It worth it, it deserve SIX Stars if possible. ... Read more

Book Description
Health & Numbers
A Problems-Based Introduction to Biostatistics
Second Edition
Chap T. Le, Ph.D.

Newly revised and updated, Health and Numbers, Second Edition serves as a concise introduction to basic statistical concepts and reasoning at a level suitable for a broad spectrum of students and professionals in medicine and allied health fields. This user-friendly resource uses real-life examples with real data to emphasize fundamental biostatistical concepts.

The book treats fundamental statistical methods with a practical, problems-based approach. It covers the nuts and bolts of elementary applied statistics for those who have no prior knowledge and experience in statistics. It provides an overview of basic ideas on standardization and rates and graphical techniques, offers more exercises than did the first edition, and features Microsoft® Excel and SAS samples, and new chapters on comparisons of means and proportions, as well as regression and correlation techniques. Health and Numbers, Second Edition strikes a balance between principles and methods of calculation that is particularly useful for students in medicine and health-related fields who are struggling with required courses in biostatistics. ... Read more

Customer Reviews (1)

Warning: Text contains many errors
+ Note: This review was originally written for another book from this author, but touches on my experience with this text as well.

It is mind-boggling how one can have so many mistakes in a textbook like this. This book was required for our Biostatistics II class, and I am really displeased by all of the mistakes. What is the worst offense is that some of the answers for test questions are wrong. For example, the one way ANOVA problem 7.21 has the wrong F-statistic: the wrong answer. Others in the class have complained about this text as well. This is simply amazing to me, and leaves me not trusting much of the text in this book.

His other book "Health and Numbers" is just as terrible; the professor that used that book for class made a list of the mistakes they found, and us students in that class found many more along the way. I ran into another statistics book that takes all of the procedures step-by-step and really made it simple for me. This book, and his other are not recommended. ... Read more

Book Description

Contents
Preface To The Third Edition
Acknowledgments

Customer Reviews (1)

Good as far as it goes
Although billed as a 'primer for health & biomedical professionals', this book is actually too basic for that. Most in the field are not undergrads, and so need the more advanced statistical measuring methods explained more thoroughly (or, in some cases, at all). There is nothing about infective disease, so those measures are also lacking.

This book feels very disorganized, with little help from the index and contents. There are much better books of this type on the market - for example, Primer of Biostatistics by Stanton A. Glantz or even Epidemiology by Leon Gordis. I'd keep looking. ... Read more

Customer Reviews (1)

Introduction to Biostatistics
One of the best texts I've come across on the subject. Lucid, clearly set out with plenty of worked examples. Not too rigorous for the beginner, yet contains enough mathematical detail for the basic concepts to beunderstood. Examples, problems and worked examples are highly relevant toreal problems in biological data analysis. ... Read more

Book Description
Emphasizing statistical concepts used in medicine, the interpretation of methods, and applications, Medical Biostatistics, Second Edition shows how biostatistical methods are important tools in managing uncertainties in medicine and the health sciences. With coverage ranging from elementary topics, such as mean and standard deviation, to advanced approaches, such as logistic regression and multivariate methods, this edition is even more far-reaching in scope than its predecessor.

New to the Second Edition

Full chapters on clinical trials, observational studies, laboratory experiments, survival analysis, and logistic regression

A new chapter on clinimetrics and evidence-based medicine

Expanded discussions on epistemic uncertainties, crossover designs, equivalence trials and studies, hazard functions, and the log-rank test

The introduction of research evidence, multilevel regression, classification, and regression trees at an elementary level

Sample size formulas for relative risk, odds ratio, and survival studies

Numerous additional examples from contemporary medical literature

Numbered steps for the many procedures and remarks

Requiring only high school algebra, this text enables a solid understanding of the statistical concepts required to critically examine medical literature, scientifically plan and carry out medical investigations, and meaningfully analyze data. ... Read more

Book Description
The first edition of the Encyclopedia of Biostatistics proved an outstanding achievement in scientific publishing. A truly international work, its coverage ranges through statistical issues pertinent to life scientists, healthcare professionals and practising statisticians.

Wiley is now pleased to announce the Second Edition of this landmark reference work publishing in February 2005.  Drawing on the expertise of the original editorial team the new edition will be revised and expanded to provide, in particular, up-to-date material on bio-informatics and statistical genetics.

This major publication is easily accessible for all those involved in statistical activities in medicine and health sciences, from health professionals who are not highly trained in statistics, through to fully qualified and experienced statisticians.

For further information on this new edition please visit: www.wileyeurope.com/go/eob

Reviews of the First Edition

“…a resource beyond compare...the author index reads like a contemporary Who's Who...nothing in biostatistics is left uncovered...unsurpassed in quality and quantity"
—British Medical Journal

"An unsurpassed addition to the statistical literature …The present scope of statistics in medical research is nowhere more manifest …the coverage is breathtaking"
—International Journal of Epidemiology ... Read more

Book Description

This book provides a solid foundation in introductory biostatistics with up-to-date methods, lucid explanations, and a modern approach. Explains commonly used biostatistical methods, such as odds and risk ratios, and Fisher's exact test, in a clear and thorough manner. Introduces equivalence testing in a variety of research settings. Presents nonparametric methods in a modern light, couched in the broader context of permutation-based methods. Provides real-world data with case studies consisting of synopses of published research. Provides step-by-step solutions to exercises, along with pertinent equations used in obtaining the solution and page numbers of relevant discussions. For health science students and professionals who need to increase their understanding of biostatistics.

Customer Reviews (3)

Am I really the only one writing a poor review???
I have to confess to being a bit surprised in the fact that I am the only one to, up until this point, write a negative review of this book.I am currently a graduate student in a biostatistics program at Tulane University and I think that my first semester biostatsinstructor summed up this book best in her stating that "I think it is clear that this book was not written by statisticians."

This book provides a number of misrepresentations of statistics and rarely provides enough information to be useful.If you give any importance to mathematical rigor this is not the book for you (I am a biostats student, not a math student, my threshold for mathematical rigor is relatively low).

If you would like to understand this subject I highly recommend your buying the book by Rosner.Rosner's book IS significantly more difficult than Blair and Taylor, but it also provides the information needed to gain any practical knowledge of the subject matter.

That said, if your hope is to breeze through a biostatistics course as to complete your MPH and you place fairly little importance on the concepts of this class (i.e. if you are taking a biostats course because you HAVE to) this is probably a good text choice.

Good Textbook, With Some Reservations
I have used other biostatistics texts before, and this is indeed one of the better ones.Generally, the explanations are clear and easy to follow, but not always.Sometimes, the author will go into far too much detail and risks losing all but the most capable students under a mountain of excessive information for an intro textbook.

Other times, the example calculations will not match up with the instructions given.For example, when doing a two-tailed test and testing for significance, you can either double the obtained p-value OR halve the critical p-value.In some cases, the author will explain a given test and discuss halving the critical p-value, but then in example calculations will double the obtained p-value without comment.This is a small example, but this type of thing happens all the time.

The appendices are excellent.For instance, the author provides both "sides" of the area under the normal curve (Z-scores and p-values) for a given half, whereas most authors require you to solve .5-n to get the other part.Again, this sounds minor, but it is a help and a timesaver.I also like how all the equations are set off in boxes, and the author does a fine job of immediately explaining what variables are what.

All in all, I like this book.I wish it left out some amount of what I consider to be excessive detail, and I also wish that all the example calculations were consistent with the instructions given.But otherwise, great book!

Clear
I am not good at statistics, but I find this text to be clear, even for me.It has also served well as a reference. ... Read more

Book Description
This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation. Introducing dynamic modeling for GLMs and containing over 1000 references and equations, Generalized Linear Models considers parametric and semiparametric approaches to overdispersed GLMs, presents methods of analyzing correlated binary data using latent variables. It also proposes a semiparametric method to model link functions for binary response data, and identifies areas of important future research and new applications of GLMs. ... Read more

Book Description
This work provides descriptions, explanations and examples of the Bayesian approach to statistics, demonstrating the utility of Bayesian methods for analyzing real-world problems in the health sciences. The work considers the individual components of Bayesian analysis.;College or university bookstores may order five or more copies at a special student price, available on request from Marcel Dekker, Inc. ... Read more

Customer Reviews (1)

Pricey, but quicker than collecting articles by yourself
Perhaps more appropriately titled _Examples in Bayesian Biostatistics_, this book is organized as a series of articles on the use of Bayesian methods in a variety of biostatistical settings.The benefit of thisapproach is that each article is written by experts who provide theirowninsights to the methodology presented.The downside is that eacharticleis written by experts, who use slightly different notation, andexhibitvarying degrees of ability to communicate their results (they areon thewhole fairly good). ... Read more

Book Description
The Secrets Series® is breaking new ground again. A two-color page layout, a portable size, and a list of the "Top 100 Secrets" in biostatistics and epidemiology help readers to better meet the challenges they face today. And, at no extra charge, purchasers also receive online access to the complete contents of the text via Elsevier's innovative STUDENT CONSULT website. Readers will still find all of the features they rely on the Secret Series® fora question-and-answer format, lists, mnemonics, and tables and an informal tone that make reference fast and easy. No matter what questions arise in practice or while preparing for boards, this new volume has the answersin print and online.
The smart way to study!
Elsevier titles with STUDENT CONSULT will help you master difficult concepts and study more efficiently in print and online! Perform rapid searches. Integrate bonus content from other disciplines. Download text to your handheld device. And a lot more. Each STUDENT CONSULT title comes with full text online, a unique image library, case studies, USMLE style questions, and online note-taking to enhance your learning experience. ... Read more