Product 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 clincal 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

Product Description
Statistics for Health Care Professionals: Working with Excel (second edition) is written in a clear, easily followed style keyed to the powerful statistical tool, Microsoft Excel 2007. It introduces the use of statistics applicable to health administration, health policy, public health, health information management, and other professions, emphasizing the logic of probability and statistical analysis in all areas. Coverage includes data acquisition, data display, basics of probability, data distributions, confidence limits and hypothesis testing, statistical tests for categorical data, tests for related and unrelated data, analysis of variance, simple linear regression, multiple regression, and analysis with a dichotomous categorical dependent variable. A glossary and section-by-section review questions round out this uniquely comprehensive and accessible text. ... Read more

Product 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 (3)

The software that accompanies this book is only intended to be functional for one year.
I used this book and accompanying software for about a year and was surprised, when opening the software, to be greeted with the message, "Your license will expire within 30 days.Please contact license@www.CTriSoft.net to renew it immediately."Neither the book, nor the accompanying CD mentions any expiration of the software.When I contacted the vendor, they offered a brief license extension, but going forward I would need to renew the license for $495 per year.When I contacted Wiley, their response was apologetic that they hadn't mentioned the limited life of the software, and that they would do nothing until the next reprinting (at an unspecified time in the future). It was unclear what they would do then.

Although there are some warts, I found the book and software to be useful.However, the book is not valuable without the software and if you plan to use the combination for more than a year, be prepared to pay several hundred dollars per annum to renew the software license.

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

Product Description
The growth of the pharmaceutical industry over the past decade is astounding, but the impact of this growth on statistics is somewhat confusing. While software has made analysis easier and more efficient, regulatory bodies now demand deeper and more complex analyses, and pharmacogenetic/genomic studies serve up an entirely new set of challenges. For more than two decades, Statistics in the Pharmaceutical Industry has been the definitive guide to sorting through the challenges in the industry, and this Third Edition continues that tradition.

Updated and expanded to reflect the most recent trends and developments in the field, Statistics in the Pharmaceutical Industry, Third Edition presents chapters written by experts from both regulatory agencies and pharmaceutical companies who discuss everything from experimental design to post-marketing studies. This approach sheds light on what regulators consider acceptable methodologies and what methods have proven successful for industrial statisticians. Both new and revised chapters reflect the increasingly global nature of the industry as represented by authors from Japan and Europe, the increasing trend toward non-inferiority/equivalence testing, adaptive design in clinical trials, global harmonization of regulatory standards, and multiple comparison studies. The book also examines the latest considerations in anti-cancer studies.

Statistics in the Pharmaceutical Industry, Third Edition demystifies the approval process by combining regulatory and industrial points of view, making it a must-read for anyone performing statistical analysis at any point in the drug approval process. ... Read more

Customer Reviews (1)

excellent collection of articles
This is a very nice collection of real world examples from the pharmaceutical industry.There are many articles here that any biostatistician in the pharmaceutical industry would find fascinating.In fact one of my former bosses, Ted Smith from Auxilium Pharmaceuticals Inc, wrote an article about testosterone supplements.Auxilium markets Testim a testosterone gel that is used as a supplement for older men with low levels of testosterone in their system. ... Read more

Product Description
This text is an easy-to-understand, application-oriented guidebook for learning the basic principles of epidemiologic investigation. Numerous opportunities are presented to apply and test learning through problems and application exercises. Answers are provided. ... Read more

Product Description
A clear, consistent, and rigorous approach to statistics at an elementary level, this book's goal is to provide a sophisticated introduction of how and why the statistics processworks. Every concept is carefully and clearly explained, enriched by a mathematical/statistical justification, and then illustrated by at least one concrete, worked example. Beginning with basic concepts, the book allows readers to acquire the ability to understand rather complicated statistical issues, such as linear regression theory and application.After introducing the sample mean and a few other descriptive statistics, the book turns to elementary probability theory, then extends to characterize samples selected from populations. It then explores the accuracy and precision of the mean value calculated from samples, and then presents the chi-square analytic technique. The remainder of the book deals with summarizing and analyzing bivariate data.For beginners interested in statistical methods to understand data analysis; these readers are employed in many areas, including Public Health, Genetics, Forestry, Molecular Biology, Epidemiology, Biophysics, medical researchers, and pre-med students. ... Read more

Customer Reviews (4)

dear GOD!
I feel sorry for anyone using this book in a class environment.I will be using it for kindling after the class, Selvin... I hate you.

Very easy to understand
I am taking the biostatistics class at UC Berkeley and for the fist time I understand statistics (I had taken a statistics course before). This book is easy to understand and easy to follow. It explains the basics of statistics with many examples. I really like this book. Now I feel prepared to take more advanced statistics.
Like the previous review, I give it 4 stars because of editorial errors.
I totally recommend this book if you want to understand the basics of statistics.

Have to Disagree with Previous review
I am also currently taking a statistics course with Selvin at Berkeley.I took another stats course before this and despite everyone RAVING about how fabulous that class was, I found it made my head spin.Everytime I felt I understood a concept was like an epiphany, unfortunately it would quickly diminish due to more complicated examples and statistical theory.

Selvin's book (as well as class) has erased the mystery for me.I find the book thorough with clearly explained concepts and multitudes of relevant examples.Probability, smobability.Linear regression, no problem.

I'm giving the book 4 stars because of the editorial mistakes, otherwise I'd have given it 5 all the way.

A horrible statistics textbook
This is the worst textbook that I have ever used for a class, hands down. I am currently taking biostatistics with Selvin at U.C. Berkeley and this book is completely unhelpful. The proofs in the book are useless and the concepts explained in the book are convoluted and confusing. There are much better statistics textbooks out there. I definitely don't recommend this text for any biostatistics course. ... Read more

Product Description

Using WinBUGS to implement Bayesian inferences of estimation and testing hypotheses, Bayesian Methods for Measures of Agreement presents useful methods for the design and analysis of agreement studies. It focuses on agreement among the various players in the diagnostic process.

The author employs a Bayesian approach to provide statistical inferences based on various models of intra- and interrater agreement. He presents many examples that illustrate the Bayesian mode of reasoning and explains elements of a Bayesian application, including prior information, experimental information, the likelihood function, posterior distribution, and predictive distribution. The appendices provide the necessary theoretical foundation to understand Bayesian methods as well as introduce the fundamentals of programming and executing the WinBUGS software.

Taking a Bayesian approach to inference, this hands-on book explores numerous measures of agreement, including the Kappa coefficient, the G coefficient, and intraclass correlation. With examples throughout and end-of-chapter exercises, it discusses how to successfully design and analyze an agreement study.

Customer Reviews (1)

agree or disagree how do we measure it
This is the scond book of Lyle Broemeling that I am reviewing for Amazon.I met him at the Joint Statistical Meetings a few years ago when he was just retiring from M.D. Anderson.in recent years M. D. Anderson has become a leader in designing Bayesian adaptive designs of clinical trials.This is mainly due to the leadership of Don Berry who came to head up the biostatistics group at M. D. Anderson several years ago when he was attracted away from Duke.Broemeling benefitted from the arrival of Berry because he was establishe there as a Bayesian and had written a book on Bayesian analysis many years earlier.

Now that he is retired from M. D. Anderson he is writing applied biostatistics texts applying Bayesian methods to specialized topics.The first one which I reviewed earlier on amazon was on diagnostic testing and this one is to analyze measures of agreement among judges.The two books are both scholarly written and authoritative and clear.They both also provide many real examples based on Lyle's vast experience at M. D. Anderson.

A few years ago I was supporting the company BioImaging in the development of their protocols for medical imaging data from patients in oncology clinical trials. I learned that an important aspect of determining the efficacy of a drug against a particular cancer tumor.This performance is usually measured by individual ranking from radiologist who read the scans over time and assess growth or shrinkage of the tumor after being treated by a drug.Typically there are two or three readers and the rating of progression or remission depends on a concensus of the radiologists assessments.

This is exactly the problem Broemeling faced at at M. D. Anderson and he has a wealth of applications in the setting of oncology trials.Broemeling details the history of the develop of methods used to reach a conclusion.He provides a wealth of examples and also includes interesting examples from sports including an analysis of a famous boxing match between Lennox Lewis and Evander Holyfield.He deals methodically with the case of two raters (where an adjudicator general resolve the conflicting cases) and then three or more raters where things get more complicated.

Modern Bayesian approaches are demonstrated using the winBugs software.Broemeling provides the code in the winBugs language to handle various examples.This approach involves Markov Chain Monte Carlo methods.Examples are explained in detail and illustrated very carefully.

Broemeling also provides a history of the various statistics used to measure agrrement between readers or judges.Another example that struck me as very interesting is a forgery case where a signature was forged to produce a fake will.Usually in forgery cases the methods are used to find differences in the signature that are large enough to assert that they came from different people.However in this example the forged signature was traced from the original persons sample signature.So in the case the objective was to show that the cases are too similar not to have been forged.We are able to do this because we can show repeated signatures from the same hand will have more variability than the traced signature. So in this case the hired statisticians showed that the two signatures are much too similar for the second one to be real and independent of each other.

Bayesian sample size estimation is also covered in the text.It is a great reference book for anyone who does oncology trials and appreciates the advantages of the Bayesian approach.The Kappa measure is the one that is given the most attention in the book. ... Read more

Product 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

Customer Reviews (1)

excellent encyclopedia
I have the first edition of this which was a six volume set.The editors are the same.Peter Armitage is a world famous biostatistician.The entries in the first edition were excellent and up to the standards set by the Encyclopedia of Statistical Sciences by Johnson, Kotz and Read.I would expect the same in the second edition and the expansion to 8 volumes is just a testament to the new terms and methodologies that have matured over the last several year. ... Read more

Product Description
Adaptive design has become an important tool in modern pharmaceutical research and development. Compared to a classic trial design with static features, an adaptive design allows for the modification of the characteristics of ongoing trials based on cumulative information. Adaptive designs increase the probability of success, reduce costs and the time to market, and promote accurate drug delivery to patients.
Reflecting the state of the art in adaptive design approaches, Adaptive Design Theory and Implementation Using SAS and R provides a concise, unified presentation of adaptive design theories, uses SAS and R for the design and simulation of adaptive trials, and illustrates how to master different adaptive designs through real-world examples. The book focuses on simple two-stage adaptive designs with sample size re-estimation before moving on to explore more challenging designs and issues that include drop-loser, adaptive dose-funding, biomarker-adaptive, multiple-endpoint adaptive, response-adaptive randomization, and Bayesian adaptive designs. In many of the chapters, the author compares methods and provides practical examples of the designs, including those used in oncology, cardiovascular, and inflammation trials.
Equipped with the knowledge of adaptive design presented in this book, you will be able to improve the efficiency of your trial design, thereby reducing the time and cost of drug development. ... Read more

Customer Reviews (3)

Comprehensive, concise, unified presentation written by a hands-on statistician with years of adaptive design experiences
There are explosions of adaptive design papers in past several years. This book alone has included about 400 references. It is very confusing to most new researchers in this field. This book use a unified approach to treat the major hypothesis test based adaptive design methods, i.e., view different methods as some forms of stagewise p-values combinations for test statistics. Chapter 1 provides overview of adaptive designs. Chapter 2 provides background for various clinical trials including superior, non-inferiority, equivalence and dose-response trials. The unified approach is presented in chapter 3 for stopping boundary determination, adjusted p-value, early futility and efficacy stopping, expected sample-size and clinical trial duration, conditional power, and futility index. All the formulations for these operating characteristics are presented in multiple-integration forms. In the next several chapters, all the integrations for the operating characteristics are carried out for particular combinations of p-values - lead to particular statistical methods for adaptive designs. In the most cases, the book avoid to using approaches from the original papers when the ideas were first proposed to avoid confusions and reduce the amount of material to be included. Chapter 7 presented another way (conditional error approach) to look at the common and different characteristics among different methods. Almost all methods for adaptive design can be reviewed as the conditional error approach. The difference is that each method uses a different conditional error function. In the chapter, different conditional error function and conditional power formulations are summarized. Chapter 8 discusses the recursive conditional error method so that it can be used for a K-stage adaptive design. Chapters 9 to 14 discuss different types of adaptive trials using the statistical methods that have been discussed in the previous chapters. These trials include sample-size reestimation, drop-loser design, biomarker adaptive design, response-adaptive randomization, adaptive treatment switch, and multiple endpoint issues. Chapters 15 and 16 discuss Bayesian adaptive approach for clinical trials. Chapter 17 talks about implementation issues. Chapter 18 is for readers who are interested in philosophical debates.

If you have not read too much adaptive design research papers, you wouldn't be confused, and you may not appreciate the unified approach in this book.

For most chapters, computer programs (SAS Macro) are provided with illustrated examples from clinical trials. However, it is not the author's intention to teach to how to implement adaptive design using SAS. The main purpose to include computer programs is to provide tools that you can use to design your adaptive trials since the software for adaptive design is very expensive (some reach [..]annual license for single user). It is not a computer book. Hence the algorithm of the computer program is usually not provided your clinical trials. However, each program is written with clear logic flows and is only about a page long. It should not be a challenge to most readers who have coding knowledge. The corresponding R functions are presented in Appendix. Because they are so similar between a SAS Macro and the corresponding R function. It is wise to put one of them in the appendix. The R functions cover the typical adaptive designs. Others can be directly translated from SAS macros without any difficulties.

There are exercises at end of chapters. Some are good, some are OK. This should be enhanced for the revision.

For some reasons, Amozon.com does not include the sample pages from the book. I am the author of book; I think it is helpful to use this feature to provide some insight for the readers. More information can be found online, where you can obtain the table of contents and the electronic computer programs. Rank it 5 starts that could be author's bias.

A SAS macro library with attached documentation and a few R functions appended
The book, going by the table of contents, provides a fairly comprehensive overview of the field of adaptive designs in drug development.
After having read it, I am somewhat disappointed. The topics are in fact all there, and the different approaches are presented. There is no real overview on how the different approaches link together though.
I think that other texts like Ting (Dose Finding in Drug Development (Statistics for Biology and Health)) do a much better job at providing the background.

The code seems quite useful, but the typesetting is fairly disastrous. Most functions and macros have many parameters, and they are listed in floating text style instead of a tabular layout, making it very hard to read.
The code is typeset in proportional font (where monospace is standard) and does not contain any comments and documentation of particular blocks.

Finally, the text comprises 27 SAS programs and only 6 R programs. The SAS programs are in the corresponding chapters, the R programs are all put at the very end of the book in its own appendix chapter. The R code is of fairly low quality, suggesting that the author is a SAS user and transcribed the code into R.
Example of some typical and not so great R code:
for(i in 1:nStgs) { TSc[i] = 0}

So the benefit of the book might be in the SAS library. It is not in the introduction to adaptive design theory and certainly not in the small R library, making the title somewhat misleading.

excellent topic, well covered, with software for implementation
This book just came out but I know a lot about it and about the author before I even got a copy.In November of last year Mark Chang coauthored a book in this Chapman and Hall series that I reviewed with praise because of the importance of the topic and the way it was demonstrated to work in a variety of real problems in pharmaceutical clinical trials.This book is even better as it goes more deeply into the methodology, the controversies and the results from simulation studies.Also it is much more practical because for every case where an application is given a SAS macro is also included to allow the reader to try the methodology for himself.In March of 2007 I actually designed a two-stage adaptive design with sample size reestimation for bioequivalence trials.I met mark at a conference where he presented much of his recent work and he was instrumental in helping me through his first book and his journal articles.This book had already gone to the publisher but he realized that this important design had overlooked.He added it when the copyedited version came to him.The design and the simulations related to it are very close to what I actually used.For those who like to program in R, he provides R code corresponding to each of the SAS macros that he gave.These programs make the new methodology readily available to interested users. The book is very comprehensive in that it covers a wide variety of applications for phase 2, phase 3 and combined phase trials.With the FDAs new initiative to speed up the drug discovery process this book will be an invaluable tool to statisticians in the pharmaceutical industry who would like to learn and apply these methods that along with the group sequential methodsare gaining favor within the FDA. ... Read more

Product Description
Delhi Univ. College of Medical Sciences, India. Encapsulates the principal concepts and methods of biostatistics, detailing critical stages of planning, conducting, and interpreting data trials that promote reliable results from conceptualization to conclusion. ... Read more

Customer Reviews (2)

If there's a better book on the subject...
...then I'd like to know what it is.

Absolutely superb textbook.
Extremely well researched with numerous examples from real case studies.
It's actually fun to read and educational at the same time.

None better, plain and simple.

Statistics made medical
I have long been looking for a book that makes biostatistics simple and readable to medical professionals. This book on Medical Biostatistics by Indrayan and Sarmukaddam (Marcel Dekker) is a very sincere attempt in making the subject of biostatistics look like a medical discipline. This is one of the objectives stated in the book, and seems to have been very adequately achieved. The language used is friendly to the medical fraternity. A large number of statistical methods have been discussed that are commonly used in medicine and health. Mathematics is minimal and explantions appeal to the common sense. Statistical fallacies are also discussed. Strongly recommended for all professionals and students of medical related disciplines who collect, disseminate or use data in any form. ... Read more

Product Description

Useful Statistical Approaches for Addressing Multiplicity Issues
Includes practical examples from recent trials

Bringing together leading statisticians, scientists, and clinicians from the pharmaceutical industry, academia, and regulatory agencies, Multiple Testing Problems in Pharmaceutical Statistics explores the rapidly growing area of multiple comparison research with an emphasis on pharmaceutical applications. In each chapter, the expert contributors describe important multiplicity problems encountered in pre-clinical and clinical trial settings.

The book begins with a broad introduction from a regulatory perspective to different types of multiplicity problems that commonly arise in confirmatory controlled clinical trials, before giving an overview of the concepts, principles, and procedures of multiple testing. It then presents statistical methods for analyzing clinical dose response studies that compare several dose levels with a control as well as statistical methods for analyzing multiple endpoints in clinical trials. After covering gatekeeping procedures for testing hierarchically ordered hypotheses, the book discusses statistical approaches for the design and analysis of adaptive designs and related confirmatory hypothesis testing problems. The final chapter focuses on the design of pharmacogenomic studies based on established statistical principles. It also describes the analysis of data collected in these studies, taking into account the numerous multiplicity issues that occur.

This volume explains how to solve critical issues in multiple testing encountered in pre-clinical and clinical trial applications. It presents the necessary statistical methodology, along with examples and software code to show how to use the methods in practice.

Customer Reviews (2)

Terrible print quality
The print quality of this book is terrible.I returned the first copy thinking I just got a bad copy.This was not the case.It looks like the book was printed as the ink was running out.Some letters are only partially there.This is a problem for a mathematical text that uses Greek as well as Roman letters.Chapman & Hall Books should be ashamed.

modern approaches to mutliple comparisions applied to the pharmaceutical industry
This is a brand new text with applications to the pharmaceutical industry.Mutiple Testing problems are of great importance to the FDA in reviewing new drug applications and also in genetics and bioinformatics.This is evident in the many recent texts on the topic.This is another one of the fine texts in the biostatistics series that Professor Shein Chow edits for Chapman & Hall/CRC.The book editors Dmitrienko, Tamhane and Bretz are well known for their work in this area and in addition to editing and organizing the text they are also major contributors to the chapters.Tamhane, Hsu and Westfall have each written recent texts on multiple testing that include the modern advances over the traditional methods of Scheffe, Tukey and Dunnett and the classical text Simultaneous Statistical Inference by Rupert Miller.Tamhane is an academic, while Dmitrienko and bretz are internationally knwo statisticians who work in the pharmaceutical industry.The first chapter of the book provides the FDA perspective and is coauthored by an FDA statistician Mohammad HuqueChapter 2 provides a broad picture of the various multiple comparison methods and is an extensive chapter written by the three editors and Brian Wiens, Peter Westfall, James Troendle and Jason Hsu.It includes at the end a section on software implementation in SAS and R.This chapter provides the foundation for the rest of the book.

Chapter 3 specializes to dose response problems that are important in phase II of clinical trial research in the pharmaceutical industry.In recent years pharmaceutical companies strive to add more and more indications on the label for a drug.In some cases this requires special phase IV trials but well-planned phase III trials that incorporate hierarchical step-down procedures can often be used to get several of the most important endpoints accepted.These multiple endpoint trials are becoming more and more common.Many of these methods control the familywise type I error rate.More general concepts such as false discovery rate make it possible to control the number of mistakes while testing a very large number of statistical hypotheses as often comes up with microarrays.

Gatekeeping procedures which generalize the hierarchical stepdown procedures are the subject of Chapter 5.Chapter 6 covers the adaptive designs that are becoming more and more common and popular.Case studies are also included.Chapter 7 is the final chapter and it covers microarray experiments and pharmacogenomics.
... Read more

Product Description
Univ. of Washington, Seattle. Provides a critical summary of research approaches to the epidemiologic study of workplace hazards. Updated to include such topics as case-cohort and case-crossover designs and statistical analysis of repeated measures data. Previous edition: c1989. DNLM: Epidemiologic Methods. ... Read more

Customer Reviews (1)

a clear book
It explains very clearly all concepts. It includes a good section on exposure and dose modelling. It includes many examples. ... Read more

Product Description
This practical guide shows why the analytic methods work and how to effectively analyze and interpret epidemiologic and medical survival data with the help of modern computer systems. The introduction presents a review of a variety of statistical methods that are not only key elements of survival analysis but are also central to statistical analysis in general. Techniques such as statistical tests, transformations, confidence intervals, and analytic modeling are presented in the context of survival data but are, in fact, statistical tools that apply to understanding the analysis of many kinds of data. Similarly, discussions of such statistical concepts such as bias, confounding, independence, and interaction are presented in the context of survival analysis as well as the basic components of a broad range of applications. ... Read more

Customer Reviews (1)

Steve Selvin's Guide to Survival
Ah, the shudder when a professor assigns his own book.But never fear, Steve Selvin, recipient of numerous teaching awards, is not publishing a book to line the faded jeans pocket, or to swell his balding curly head.Rather, it's just a practical way of printing his lecture notes and homeworks. Furthermore, its rare that a top research university professor has time to write textbooks, so the burden falls to the mediocre. Selvin somehow manages to find the time and save us from so many other books that screw up statistics. ... Read more

Product Description
The first edition of Basic Statistics and Pharmaceutical Statistical Applications successfully provided a practical, easy-to-read, basic statistics book. This second edition not only updates the previous edition, but expands coverage in the area of biostatistics and how it relates to real-world professional practice. Taking you on a roller coaster ride through the world of statistics, Dr. De Muth clearly details the methodology necessary to summarize data and make informed decisions about observed outcomes.

What's new or different in the Second Edition?

New chapters cover

Product Description
Provides descriptions, explanations, and examples of the Bayesian approach to statistics;demonstrating the utility of the Bayesian methods for analyzing real-world problems in the health sciences. Bayesian Biostatistics elucidates Bayesian methodology by presenting actual health-related data sets and performing data analyses begins by discussing Bayesian methods at an introductory level and proceeds to cover state-of-the-art techniques focuses on substantive medical and scientific questions uses modern, timesaving developments in computation recommends strategies to resolve current controversies in biostatistics and more! ... Read more

Customer Reviews (2)

nice book of example of how real problems in biostatistics are handled by the Bayesian approach
Don Berry is a Professor of Statistics at the MD Anderson School of Medicine and Cancer Research Center at the Univerity of Texas in Houston and a strong advocate of the Bayesian approach in clinical trials and other medical and biostatistical applications.He has written elementary and advanced texts on Bayesian methods and is eloquent both as a speaker and author.

As editor of this book he has assembled a fine collection of articles that clearly demonstrate the practical value of the Bayesian approach to a wide variety of medical and other biological problems.

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

Product Description
Social epidemiology is the study of how social interactions—social norms, laws, institutions, conventia, social conditions and behavior—affect the health of populations. This practical, comprehensive introduction to methods in social epidemiology is written by experts in the field. It is perfectly timed for the growth in interest among those in public health, community health, preventive medicine, sociology, political science, social work, and other areas of social research.

Topics covered are:

• Introduction: Advancing Methods in Social Epidemiology
• The History of Methods of Social Epidemilogy to 1965
• Indicators of Socioeconomic Position
• Measuring and Analyzing 'Race'
• Racism and Racial Discrimination
• Measuring Poverty
• Measuring Health Inequalities
• A Conceptual Framework for Measuring Segregation and its Association with Population Outcomes
• Measures of Residential Community Contexts
• Using Census Data to Approximate Neighborhood Effects
• Community-based Participatory Research: Rationale and Relevance for Social Epidemiology
• Network Methods in Social Epidemiology
• Identifying Social Interactions: A Review, Multilevel Studies
• Experimental Social Epidemiology: Controlled Community Trials
• Propensity Score Matching Methods for Social Epidemiology
• Natural Experiments and Instrumental Variable Analyses in Social Epidemiology
• and Using Causal Diagrams to Understand Common Problems in Social Epidemiology.

"Publication of this highly informative textbook clearly reflects the coming of age of many social epidemiology methods, the importance of which rests on their potential contribution to significantly improving the effectiveness of the population-based approach to prevention. This book should be of great interest not only to more advanced epidemiology students but also to epidemiologists in general, particularly those concerned with health policy and the translation of epidemiologic findings into public health practice. The cause of achieving a ‘more complete’ epidemiology envisaged by the editors has been significantly advanced by this excellent textbook."
—Moyses Szklo, professor of epidemiology and editor-in-chief, American Journal of Epidemiology, Johns Hopkins University

"Social epidemiology is a comparatively new field of inquiry that seeks to describe and explain the social and geographic distribution of health and of the determinants of health. This book considers the major methodological challenges facing this important field. Its chapters, written by experts in a variety of disciplines, are most often authoritative, typically provocative, and often debatable, but always worth reading."
—Stephen W. Raudenbush, Lewis-Sebring Distinguished Service Professor, Department of Sociology, University of Chicago

"The roadmap for a new generation of social epidemiologists. The publication of this treatise is a significant event in the history of the discipline."
—Ichiro Kawachi, professor of social epidemiology, Department of Society, Human Development, and Health, Harvard University

"Methods in Social Epidemiology not only illuminates the difficult questions that future generations of social epidemiologists must ask, it also identifies the paths they must boldly travel in the pursuit of answers, if this exciting interdisciplinary science is to realize its full potential. This beautifully edited volume appears at just the right moment to exert a profound influence on the field."
—Sherman A. James, Susan B. King Professor of Public Policy Studies, professor of Community and Family Medicine, professor of African-American Studies, Duke University ... Read more

Product 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® for—a 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 answers—in 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 * Helps readers understand the applications of complex statistics to medicine and the analysis of factors determining the frequency and distribution of disease in specific populations.* Includes a list of the "Top 100 Secrets" to keep in mind during a rotation or residency. * Features a compact trim size (5 1/4" x 8 1/2") for enhanced portability. * Makes information easier to find with a two-color page layout and "Key Points" boxes. * Identifies useful websites to make it easy to find additional information on a specific topic, and provides live links in the online version. * Uses bulleted lists, tables, short answers, and a highly detailed index to expedite reference. * Features pearls, tips, memory aids, and "secrets" from the experts. ... Read more

Customer Reviews (1)

Great book
Well-written and concise.Nordness and his cadre of authors successfully demystify the challenging concepts of epidemiolgy and biostats.I am acing all my public health exams, thanks to this book.My only regret is that I didn't pick it up sooner! ... Read more