Book Description

First published in 1986, this unique reference to clinical experimentation remains just as relevant today. Focusing on the principles of design and analysis of studies on human subjects, this book utilizes and integrates both modern and classical designs. Coverage is limited to experimental comparisons of treatments, or in other words, clinical studies in which treatments are assigned to subjects at random. ... Read more

Reviews (3)

now a classic and still a great reference
This book was first published in 1986. As Fleiss states in his preface, the intention is to fill a gap in the standard texts on experimental designs by emphasizing and illustrating those that are useful in clinical studies. This book was clearly marketed for the rapidly growing and highly regulated pharmaceutical industry. In addition to the classic experimental designs, Fleiss covers cross-over designs and repeated measure designs that are important in clinical trials. He writes clearly and deals with the important issues in clinical trials including potential biases, blinding, randomized controls, multiple comparisons and repeated measures. The book starts off with a chapter that emphasizes the effect of measurement error and also provides some simple experiments on reliability of measurements.

There is a wealth of methods included, many different designs and various parametric and nonparametric analysis techniques. It is aimed at biostatisticians in the pharmaceutical industry and the medical research field. The book is very much suited for an advanced undergraduate or graduate level course for students majoring in statistics or biostatistics. The level of mathematics is high but not excessively used. Mathematical results on sample size determination are deferred to an appendix.

The Wiley editors choose only successful books to be included in their Classics Library series. The intent of the Classics series is to take popular books by distinguished authors and create a paperback edition that may be more affordable than the hardcovered edition still in print. It is not a revision of the book. This book entered the Classics series in 1999.

It is a great reference source and I plan to consult it a great deal in the future. The only drawback to it that I see is that it is not up to date. The last 15 years has seen many advances in group sequential methods, Bayesian designs and longitudinal data analysis that this text misses. So Fleiss' book is not one stop shopping for a clinical biostatistician but it does offer a lot and presents it eloquently.

With regard to reviewer Izadi's comments on Amazon, I think the appropriate way to ask this question is really to write the author. Since it is here in print for the readers, I will attempt a reply. I think there is a misinterpretation of the terminology. When Fleiss refers to mean logarithms he is not referring to the population means on the log scale but rather the logarithm of the population mean on the original scale. With the latter interpretation equation 3.25 makes perfect sense. It is the former interpretation of the parameters that the reviewers point addresses. The importance in the example is to demonstrate the lack of robustness of t or F tests to non-normal (e.g. lognormal) data and to show that tests and confidence intervals can still be accomplished using the normal theory after the transformation. The key point is that it is the ratio of the parameters that is transformed into differences of the log of the parameters.

A must for biostatisticians
This is the standard text on this subject. Recommend you have at least a Master's degree in statistics to take full advantage of this book. This book is too technical for non-statisticians, although they may get some useful infomation from the non-statistical discussions.

A question from the autour
Dear Sirs I do not know if I can use this part as a tool for contacting the autour or not; however please excuse me if I have not used it properly: I am a student of epidemiology, and presently we are studying the following book: The Design and Analysis of Clinical Experiments; Joseph L. Fleiss; John Wiley & Sons; 1986. But on page 67 it seems that there is some misunderstandings: When we do a log transformation, in fact we are changing (or shifting) the previous distribution to a normal distribution. Without any doubts in this transformation the means of our previous distributions do not transfer to the means of the new distributions! In fact these are the medians of the previous distributions which are transferred to the place of the means of new distributions (of course if we presume that the new distributions are almost perfectly normal) and by finding the confidence interval of the difference of the means of new distributions (lambda1 - lambda2) we are finding the CI of ratio Median1/Median2. In this way it seems reasonable that the formula 3.25 be changed to Median1/ Median2. It would be very kind of you if you help me in this problem!

With best regards Dr. Shahrokh Izadi ... Read more

Book Description

Cross-over trials are an important class of design used in the pharmaceutical industry and medical research, and their use continues to grow. Cross-over Trials in Clinical Research, Second Edition has been fully updated to include the latest methodology used in the design and analysis of cross-over trials. It includes more background material, greater coverage of important statistical techniques, including Bayesian methods, and discussion of analysis using a number of statistical software packages.
* Comprehensive coverage of the design and analysis of cross-over trials.

* Each technique is carefully explained and the mathematics is kept to a minimum.

* Features many real and original examples, taken from the author's vast experience.

* Includes discussion of analysis using SAS, S-Plus and, GenStat, StatXact and Excel.

* Written in a style suitable for statisticians and physicians alike.

* Computer programs to accompany the examples in the book can be downloaded from the Web

Primarily aimed at statisticians and researchers working in the pharmaceutical industry, the book will also appeal to physicians involved in clinical research and students of medical statistics. ... Read more

Book Description

Presents statistical techniques frequently used in medical research in an understandable format for the non-mathematician. Since the third edition, there have been many developments in statistical techniques. The fourth edition aims to provide the medical statistician with an accessible guide to these techniques and to reflect the extent of their usage in medical research.

Uses examples selected almost entirely from medical research projects

Statistical topics presented reflect the frequency of their usage in medical usage

The new edition radically reorganizes the text coppared with previous editions ... Read more

Reviews (3)

Good Primer of Medical Statistical Theory
This edition if the classic text is extensively revised from previous editions. It offers a good background of theoretical considerations in biomedical statistics. It is particularly useful for the non-statistician physician who is involved in clinical trials.

Statistical Methods in Medical Research
My book has not arrived. Please let me know where it is. Your company does not have any contact numbers.

Begin to learn Statistics through this book
For a beginner, it is really an excellent book. It almost has included all of the most important statistical methods practiced in medical research without pricing at detail loss. Its way of lucid writing and rich examples can help a beginner read through the whole book with some joy. For a senior one on this field, I still think that he/she can take it as a handbook and believe he can find some clue before he pays more attention to another throughly reading.
The new edition adds a lot of new contents especially the Bayes' theroy which is becoming a fashion in nowadays. ... Read more

Book Description

Struggling with focus groups questions? Asking the right questions is critical in focus group interviewing. Developing Questions in a Focus Group describes a practical process for identifying powerful themes and offers an easy-to-understand strategy for translating those themes into questions. Richard A. Krueger suggests ways of categorizing, phrasing, and sequencing focus group questions. Going beyond material presented in his earlier books, Krueger shares ideas for questions that get participants actively involved in the focus group interview by asking participants to make lists, create report cards, sort pictures, draw, cut and paste, or participate in a mini-debate. The results of these activities not only yield insightful information but are also interesting and fun. This book helps make the process of developing good questions doable by outlining a process and offering many examples. After reading this book, your focus groups will never be the same.

Book Description

Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies. ... Read more

Book Description

Both humanitarian and commercial considerations have spurred intensive search for methods to reduce the time and cost required to develop new therapies. The identification and use of surrogate endpoints, i.e., measures that can replace or supplement other endpoints in evaluations of experimental treatments or other interventions, is a general strategy that has stimulated both enthusiasm and skepticism. Surrogate endpoints are useful when they can be measured earlier, more conveniently, or more frequently than the "true" endpoints of primary interest. Regulatory agencies around the globe, particularly in the United States, Europe, and Japan, are introducing provisions and policies relating to the use of surrogate endpoints in registration studies. But how can one establish the adequacy of a surrogate? What kind of evidence is needed, and what statistical methods portray that evidence most appropriately?This book offers a balanced account on this controversial topic. The text presents major developments of the last couple of decades, together with a unified, meta-analytic framework within which surrogates can be evaluated from several angles. Methodological development is coupled with perspectives on various therapeutic areas. Academic views are juxtaposed with standpoints of scientists working in the biopharmaceutical industry as well as of colleagues from the regulatory authorities. Tomasz Burzykowski is Assistant Professor of Biostatistics at the Limburgs Universitair Centrum in Belgium. Dr. Burzykowski has published methodological work on the analysis of survey data, meta-analyses of clinical trials, and validation of surrogate endpoints. He is a co-author of numerous papers applying statistical methods to clinical data in different disease areas (cancer, cardiovascular diseases, dermatology, orthodontics). Geert Molenberghs is Professor of Biostatistics at the Limburgs Universitair Centrum in Belgium. Dr. Molenberghs published methodological work on surrogate markers in clinical trials, categorical data, longitudinal data analysis, and on the analysis of non-response in clinical and epidemiological studies. He serves as Joint Editor for Applied Statistics (2001-2004) and is President of the International Biometric Society (2004-2005). He was elected Fellow of the American Statistical Association and received the Guy Medal in Bronze from the Royal Statistical Society.Marc Buyse founded the International Drug Development Institute in 1991. He is Past President of the International Society for Clinical Biostatistics, Past President of the Quetelet Society, and Past Board Member of the Society for Clinical Trials. He is currently the Executive Director of IDDI (International Drug Development Institute) and Associate Professor of biostatistics at the Limburgs Universitair Centrum, Center for Statistics, Diepenbeek, Belgium. He has published extensively in the fields of biostatistics and oncology. His research interests include meta-analysis, surrogate endpoints, statistical detection of fraud, and the design and statistical analysis of clinical trials. ... Read more

Book Description

Hardly a week goes by without a newspaper headline or an evening news report detailing a mishap or scandal in the world of clinical research. An increasingly informed public demands speedy breakthroughs in treatment while eyeing warily the risks of participation in clinical trials. The nation’s most prestigious medical centers suffer record fines for research misconduct and the embarrassment that goes with it. Against this backdrop those in the trenches of clinical research work under heightening pressure and scrutiny. More than ever this field demands an unprecedented level of knowledge and understanding.

Clinical Research: What It Is and How It Works will provide you with a fundamental yet comprehensive understanding of all phases of the clinical research process. Every aspect of clinical research from program design, regulatory issues, ethical considerations, to IRB roles and functions, quality controls, financial management, and more are explained in clear, concise language. Whether you are a seasoned researcher or a brand new member of an IRB, this book will provide a clear, thorough perspective on the clinical research process. ... Read more

Book Description

This brand new second edition of our top-selling manual has doubled in size to address current and emerging issues that are critical to our system of human subject protection oversight. Protecting Study Volunteers in Research is a suggested educational resource by NIH and FDA (source: NIH Notice OD-00-039, 2000, page 37841, Federal Registry 2002) and was designed to help organizations provide the highest standards of safe and ethical treatment of study volunteers. This manual will be routinely referenced for ethical considerations and insights, and for a comprehensive review of regulations and guidelines not conveniently found elsewhere.

Protecting Study Volunteers in Research has become required reading in many academic institutions, IRBs and investigative sites and is a suggested training resource by regulatory agencies and research sponsors. Biopharmaceutical and CRO companies have also made this manual mandatory reading for their staff.

Written by Cynthia Dunn, M.D. of Western Institutional Review Board and Gary Chadwick, PharmD., M.P.H. of the University of Rochester, Protecting Study Volunteers in Research has been developed in accordance with ACCME. Readers can apply for CME credits or nursing contact hours. An exam is provided with each manual and is also available online.

Book features:

- Conflict of interest and disclosure
- Participant Recruitment and Retention in Clinical Trials
- Research with Secondary Subjects, Tissue Banks, Repositories, Databases and Records Review
- Historical perspectives on human subject research
- Updated ethics and federal regulations
- Roles and responsibilities of institutions and independent sites
- Roles and responsibilities of investigators and study staff ... Read more

Book Description

Doing Science offers a rare compendium of practical advice based on how working scientists pursue their craft. It covers each stage of research, from formulating questions and gathering data to developing experiments and analyzing results and finally to the many ways for presenting results. Drawing on his extensive experience both as a researcher and a research mentor, Ivan Valiela has written a lively and concise survey of everything a beginning scientist needs to know to succeed in the field. He includes chapters on scientific data, statistical methods, and experimental designs, and much of the book is devoted to presenting final results. He gives valuable suggestions for improving scientific writing, for preparing scientific talks, and devotes three chapters to hands-on advice for presenting data in charts, tables, and graphs. Anyone beginning a scientific career, or anyone who advises students in research, will find Doing Science an invaluable source of advice. ... Read more

Book Description

Generalized linear models provide a unified theoretical and conceptual framework for many of the most commonly used statistical methods. In the ten years since publication of the first edition of this bestselling text, great strides have been made in the development of new methods and in software for generalized linear models and other closely related models.Thoroughly revised and updated, An Introduction to Generalized Linear Models, Second Edition continues to initiate intermediate students of statistics, and the many other disciplines that use statistics, in the practical use of these models and methods. The new edition incorporates many of the important developments of the last decade, including survival analysis, nominal and ordinal logistic regression, generalized estimating equations, and multi-level models. It also includes modern methods for checking model adequacy and examples from an even wider range of application. Statistics can appear to the uninitiated as a collection of unrelated tools. An Introduction to Generalized Linear Models, Second Edition illustrates how these apparently disparate methods are examples or special cases of a conceptually simple structure based on the exponential family of distribution, maximum likelihood estimation, and the principles of statistical modelling. ... Read more

Reviews (4)

the most clearly written book on the topic
My copy of the second edition just arrived yesterday and it is even better than the first edition (which was fantastic). The logical organization and clarity of writing make this book a 'must have' for any statistician's library. I'd give it 6 stars if I could. Readers should also check out McCulloch and Searle's 'Generalized, Linear and Mixed Models'.

Excellent concept - Execution could be better
I wish somebody would write a concise tutorial of the matematics required for an "intermediate" book such as Dobson's. Undoubtedly for someone whose acquaintence with modern statitical methods is more current this book is a gem. For someone like myself who wants a refresher and whose math is a bit rusty it leaves something to be desired. Some of the theoretical derivations in chapters 3 and 4 (keys to the understanding of the rest of the book) would be improved by a bit more detail and a thoroughly worked example. A major shortcoming is the lack of answers to the excercises; I don't see how the book was published without them. If the book was 100 pages longer with the addition of the aforementioned material, I would have given it a five star rating.

recommended for applications and clarity
...

Bill recommended Dobson's text because of her clear writing style and many useful examples. Dobson also places the theory in the context of the general exponential family of distributions. As I knew that the second edition was about to come out I waited for it.

The wait seems to have been very worthwhile. The second edition is a real bargin.... She has updated it with the many advances that have occurred over the past 12 years since the first edition was printed. This edition now includes some discussion of generalized additive models, broader coverage of applications as survival analysis, GEE, multi-level models and nominal and ordinal logistic regression have been added. It now offers the reader more applications in a wider variety of disciplines and includes modern approaches to diagnostic checking of the models.

As with the first edition, exploratory techniques are emphasized particularly graphical methods. The goal is to unify the apparently disparate statistical techniques that students are exposed to, into one general modeling framework.

It includes a nice up-to-date bibliography and recent advanced results on longitudinal models. The level is intermediate statistics with introductory statistics and linear models taken to be prerequisites. Students are also required to have some familiarity with calculus and linear algebra.

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This book provides a surprisingly brief and gentle, yet thorough, introduction to the subject of modeling dependent variables that are not continuous (see note below). The reader, who should be familiar with calculus-based probability, may initially find it frustrating that the actual practice of modeling nominal data is not discussed until the last two chapters (of 9). However, the cause for delaying the discussion of these models is to introduce the terminology and methodology of generalized linear models through more familiar linear regression models.

Thus, while this book is not ideal for someone who wants to jump right into the thick of building logistic, loglinear, or other models for nominal data, it is quite suitable for those wishing a thorough introduction to the practice of generalized linear modeling. For greater detail, a thicker book like McCullagh & Nelder's _Generalized Linear Models_ would be suitable.

Note: While the term "Generalized Linear Models" includes linear regression models (i.e., models for continuous dependent variables), reading this book is not the easiest way to be introduced to regression. A better starting point would be Draper & Smith's _Applied Regression Analysis_ or Weisberg's _Applied Linear Regression_. ... Read more

Book Description

Praise for the first edition of Research Methods in Health:

"Professor Bowling should be congratulated on her achievement in producing such a substantial overview of the topic." - International Journal for Quality in Health Care

"...a brilliantly clear documentation of different philosophies, approaches and methods of research about health and health services. Laid out in an accessible and manageable way, it covers an enormous amount of material without sacrificing thoroughness...I would recommend it to a broad readership." - MIDIRS Midwifery Digest

"Professor Ann Bowling is not only a superb and illuminating conference presenter - she also writes exceptional books. This major research textbook is as good as an introduction to the field as you are likely to find." - The International Journal of Social Psychiatry

"...an easy to read book with excellent background information on the theory and practice of research. A summary of main points, key terms and recommended reading follows each chapter and there is a useful glossary of terms at the end of the book for quick reference...I particularly liked the checklists when undertaking literature reviews and writing research proposals." - British Journal of Health Care Management

This new edition of Ann Bowling's well-known and highly respected text has been thoroughly revised and updated to reflect key methodological developments in health research. It is a comprehensive, easy to read, guide to the range of methods used to study and evaluate health and health services. It describes the concepts and methods used by the main disciplines involved in health research, including: demography, epidemiology, health economics, psychology and sociology.

The research methods described cover the assessment of health needs, morbidity and mortality trends and rates, costing health services, sampling for survey research, cross-sectional and longitudinal survey design, experimental methods and techniques of group assignment, questionnaire design, interviewing techniques, coding and analysis of quantitative data, methods and analysis of qualitative observational studies, and types of unstructured interviewing.

With new material on topics such as cluster randomization, utility analyses, patients' preferences, and perception of risk, the text is aimed at students and researchers of health and health services. It has also been designed for health professionals and policy makers who have responsibility for applying research findings in practice, and who need to know how to judge the value of that research. ... Read more

Reviews (1)

Too Much and Too Little
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I am studying epidemilogical methods. I used this book one year ago for an introductory course. I did not enjoy the book, and my group (8) wanted their money back. I stopped reading the assignments out of the book half way through the course. The alternative readings were longer, had more depth, and were more fun.

This book is a worldwind tour of health research methods. That's the problem. They try to cram it all in, in one book. The writting is therefore quick and dry : p

I want to say something nice: You could use this book as a mini-mini-mini encyclopedia. If you were reading an article and found a study design that you are not familiar with, you could consult this book for the 30 second overview of a method : )

If a professor ever asks you to buy this book, remember: you will likely never use this book again after your course. Borrow or buy a second hand copy. Even better, go to the library and read it there. Or how about skipping these readings alltogether? ; ) ... Read more

Book Description

This easy-to-read reference book provides a practical approach for dealing with the legal and regulatory compliance issues involved in human research. Covering a broad range of topics, such as consent, confidentiality, subject recruitment and selection, the role of the investigator and Institutional Review Board, it offers timely and useful strategies for achieving regulatory compliance while reducing liability. In addition, insurance, quality management, accreditation, and risk management are topics examined in the book. The practical insights found in this volume are not found in other books on the subject. Clinical Trials and Human Research is a practical tool to help anyone involved in clinical research. ... Read more

Book Description

Critically acclaimed and resoundingly popular in its first edition, Modelling Survival Data in Medical Research has been thoroughly revised and updated to reflect the many developments and advances--particularly in software--made in the field over the last 10 years. Now, more than ever, it provides an outstanding text for upper-level and graduate courses in survival analysis, biostatistics, and time-to-event analysis.The treatment begins with an introduction to survival analysis and a description of four studies that lead to survival data. Subsequent chapters then use those data sets and others to illustrate the various analytical techniques applicable to such data, including the Cox regression model, the Weibull proportional hazards model, and others. This edition features a more detailed treatment of topics such as parametric models, accelerated failure time models, and analysis of interval-censored data. The author also focuses the software section on the use of SAS, summarising the methods used by the software to generate its output and examining that output in detail.Profusely illustrated with examples and written in the author's trademark, easy-to-follow style, Modelling Survival Data in Medical Research, Second Edition is a thorough, practical guide to survival analysis that reflects current statistical practices. ... Read more

Reviews (1)

Good introduction
A well-written introductory book. Broad range of material make it a good reference for new comers in survival analysis. ... Read more

Book Description

This text enables biomedical researchers to use a number of advanced statistical methods that have proven valuable in medical research, and uses a statistical software package (Stata® ) to avoid mathematics beyond the high school level. Intended for people who have had an introductory course in biostatistics, the volume emphasizes the assumptions underlying each method, using exploratory techniques to determine the most appropriate method.It presents results in a way that will be readily understood by clinical colleagues. Numerous real examples from medical literature and graphical methods are used to illustrate these techniques. ... Read more

Reviews (4)

Very useful during statistics class
I used this book as the text for a biostatistics class that used STATA as the statistitical package. I found the organization, problems, and the STATA output the book provides, all very helpful. In addition, as I moved systematically through the book, the tips regarding using the STATA features were key to my learning many of the practical aspects of the STATA program.

Useful in conjuction with the manuals
As a non-statistician with some stat background, I find Dupont book a delightful book. It is packed with interesting and useful information. It starts at t-test and ends with GEE models, covering Cox model with time covariates along the way. But as the author noted, the book assumes some statistical knowledge and access to STATA maual. One minor note: While the book introduction asserts that it only assumes "high school mathematics" knowldege, the high school the author attended must be very different than the one I went to.

Buy this book if you like problem based learning
I have had the pleasure of using this book during a biostatistics level two course this year. The book is structured to assist in the course work in statistics using STATA. It is user friendly and gives mathematical explanations when appropriate but without losing the reader with too many equations. The book's approach uses problem based learning along with explanatory text which I found essential in learning to navigate STATA along with learning and understanding logistic regression, poisson regression etc. The best aspect of the book is the STATA output to assist with the problem solving. The book is a very good choice as an interactive tool for understanding advanced statistics using STATA.

Do not buy this book for learning STATA or methods
I decided to buy this book since this is a new book on teaching how to use STATA on advanced statistic methods. After I browsed this book, I do not think that this is a well-organized book. It does not show you how to use the latest and easiest STATA procedures to do analysis. Theory parts of statistic methods are hard to be read and even not as good as the remarks of STATA Reference. I am totally disappointed. ... Read more

Reviews (3)

Maybe for the APA style...
I was deeply disappointed with the book. The tables look as done with a typewriter, good for those missing that 70's thesis. Apparently nobody told the authors that p-values are no longer to be reported as p<0.05, but with their full value. And finally, there is no "clever" solution to more complex tables, but just tons of tables with pretty standard results. What is reported in the tables is not widely applicable too. In my area - epidemiology - we do not report standard errors, we report confidence intervals. We also do not report mean squares, f-values, or t-values, or chi-squared-values and so on - we report only the full p-values. If you're not into APA, look elsewhere.

No more puzzling over tables!
This is an invaluable resource for anyone who needs to present their research results in APA style. This is not a statistics text but rather a manual for generating tables. Each chapter focuses on a different statistic and includes a "play it safe" comprehensive table as well as several variations. Well-organized, practical, and concise.

A Must for Students and Professionals Using APA Style
This book has been needed for twenty years. Students and professional researchers who write dissertations and manuscripts using APA style have desperately needed this very helpful resource. The book illustrates standard presentation tables for more than twenty types of standard statistical tests. The concept of "Play It Safe" tables will save researchers hundreds of hours of time. The table illustrations are clear and precise depending on the focus of the data to be presented. The few words that are written prior to presenting a table are helpful in clarifying the data contained in the tables. One small problem is noted. It would have been helpful to include how APA style recommends reporting statistical data in paragraph form in this book also. Despite this omission, I still give this book 5 stars. ... Read more

Book Description

Emphasis on clustering of data of gene tissues
* Includes new research findings and activities in molecular biology
* Highlights the important general field of bioinformatics and genomics and discusses the impact of microarray analysis on both ... Read more

Book Description

This revised and updated edition is an indespensable resource for health researchers. It draws on the most current findings in survey design, marketing research, health services research, and cognitive psychology to provide comprehensive guidance on designing and conducting health surveys. Special emphasis is placed on the complexities of the ever-changing health care environment.

... Read more