Product Description
An essential introductory text linking traditional biostatistics with bayesian methods

In recent years, Bayesian methods have seen an explosion of interest, with applications in fields including biochemistry, ecology, medicine, oncology, pharmacology, and public health. As an interpretive system integrating data with observation, the Bayesian approach provides a nuanced yet mathematically rigorous means of conceptualizing biomedical statistics--from diagnostic tests to DNA evidence.

Biostatistics: A Bayesian Introduction offers a pioneering approach by presenting the foundations of biostatistics through the Bayesian lens. Using easily understood, classic Dutch Book thought experiments to derive subjective probability from a simple principle of rationality, the book connects statistical science with scientific reasoning. The author shows how to compute, interpret, and report Bayesian statistical analyses in practice, and illustrates how to reinterpret traditional statistical reporting--such as confidence intervals, margins of error, and one-sided p-values--in Bayesian terms. Topics covered include:

• Probability and subjective probability
• Distributions and descriptive statistics
• Continuous probability distributions
• Comparing rates and means
• Linear models and statistical adjustment
• Logistic regression and adjusted odds ratios
• Survival analysis
• Hierarchical models and meta-analysis
• Decision theory and sample size determination

The book includes extensive problem sets and references in each chapter, as well as complete instructions on computer analysis with the versatile SAS and WinBUGS software packages as well as the Excel spreadsheet program. For professionals and students, Biostatistics: A Bayesian Introduction offers an unique, real-world entry point into a remarkable alternative method of interpreting statistical data. ... Read more

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Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research, such as cancer. It presents a broad overview of statistical inference, clustering, and classification problems in two main high-throughput platforms: microarray gene expression and phylogenic analysis.

The book explores Bayesian techniques and models for detecting differentially expressed genes, classifying differential gene expression, and identifying biomarkers. It develops novel Bayesian nonparametric approaches for bioinformatics problems, measurement error and survival models for cDNA microarrays, a Bayesian hidden Markov modeling approach for CGH array data, Bayesian approaches for phylogenic analysis, sparsity priors for protein-protein interaction predictions, and Bayesian networks for gene expression data. The text also describes applications of mode-oriented stochastic search algorithms, in vitro to in vivo factor profiling, proportional hazards regression using Bayesian kernel machines, and QTL mapping.

Focusing on design, statistical inference, and data analysis from a Bayesian perspective, this volume explores statistical challenges in bioinformatics data analysis and modeling and offers solutions to these problems. It encourages readers to draw on the evolving technologies and promote statistical development in this area of bioinformatics.

Product Description
Analytic procedures suitable for the study of human disease are scattered throughout the statistical and epidemiologic literature. Explanations of their properties are frequently presented in mathematical and theoretical language. This well-established text gives readers a clear understanding of the statistical methods that are widely used in epidemiologic research without depending on advanced mathematical or statistical theory. By applying these methods to actual data, Selvin reveals the strengths and weaknesses of each analytic approach. He combines techniques from the fields of statistics, biostatistics, demography and epidemiology to present a comprehensive overview that does not require computational details of the statistical techniques described.
For the Third Edition, Selvin took out some old material (e.g. the section on rarely used cross-over designs) and added new material (e.g. sections on frequently used contingency table analysis). Throughout the text he enriched existing discussions with new elements, including the analysis of multi-level categorical data and simple, intuitive arguments that exponential survival times cause the hazard function to be constant. He added a dozen new applied examples to illustrate such topics as the pitfalls of proportional mortality data, the analysis of matched pair categorical data, and the age-adjustment of mortality rates based on statistical models. The most important new feature is a chapter on Poisson regression analysis. This essential statistical tool permits the multivariable analysis of rates, probabilities and counts. ... Read more

Customer Reviews (1)

excelente tool
the book is indispensable for those working in the field of epidemiology applied to research and development of evidence-based interventions for those physicians who are interested in evidence-based medicine ... Read more

Product Description
The second volume in the Wiley reference series in Biostatistics.
Featuring articles from the prestigious Encyclopedia of Biostatistics, many of which have been fully revised and updated to include recent developments, Biostatistics in Clinical Trials also includes up to 25ewly commissioned material reflecting the latest thinking in:

• Bayesian methods
• Benefit/risk assessment
• Cost-effectiveness
• Ethics
• Fraud

With exceptional contributions from leading experts in academia, government and industry, Biostatistics in Clinical Trials has been designed to complement existing texts by providing extensive, up-to-date coverage and introducing the reader to the research literature.
Offering comprehensive coverage of all aspects of clinical trials Biostatistics in Clinical Trials:

• Includes concise definitions and introductions to numerous concepts found in current literature
• Discusses the software and textbooks available
• Uses extensive cross-references helping to facilitate further research and enabling the reader to locate definitions and related concepts

Biostatistics in Clinical Trials offers both academics and practitioners from various disciplines and settings, such as universities, the pharmaceutical industry and clinical research organisations, up-to-date information as well as references to assist professionals involved in the design and conduct of clinical trials. ... Read more

Product Description
Duke Univ., Durham, NC. Examines pharmacokinetic models, survival models, methods of improving adjustments for publication bias, group judgments and statistical computer software. Primarily a reference book that relies heavily on examples. Written for applied statisticians, and students of statistics and biostatistics. ... Read more

Customer Reviews (1)

Bayesian approach to meta-analysis
Dalene Stangl and Don Berry are two of the leading researchers on Bayesian methods and have made major contributions to medical applications. Here they have compiled a collection of excellent papers on recent research into the Bayesian approach to meta-analyses which now includes examination of heterogeneity through the use of random effects models. They contribute an introductory overview chapter and have compiled a number of very interesting state-of-the-art papers by leading researchers. Particularly interesting is the paper by Scott Berry (Don's son) who provides an analysis to show that controversy between meta-analyses and large clinical trials can be resolved through consideration of the study-to-study variability not considered in fixed effects analyses.
The text can be used for a modern course on Bayesian Meta Analysis. I just took a one-day short course from Dalene on this topic at the joint statistical meetings in Indianapolis. She gave an effective presentation using material from several of the papers in the book.

... Read more

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These conferences are held every five years. This book contains papers by several prominent biostatisticians which were inspired by the Second Seattle Symposium in Biostatistics.

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Considered highly exotic tools as recently as the late 1990s, microarrays are now ubiquitous in biological research. Traditional statistical approaches to design and analysis were not developed to handle the high-dimensional, small sample problems posed by microarrays. In just a few short years the number of statistical papers providing approaches to analyzing microarray data has gone from almost none to hundreds if not thousands. This overwhelming deluge is quite daunting to either the applied investigator looking for methodologies or the methodologist trying to keep up with the field. DNA Microarrays and Related Genomics Techniques: Design, Analysis, and Interpretation of Experiments consolidates discussions of methodological advances into a single volume.

The book’s structure parallels the steps an investigator or an analyst takes when conducting and analyzing a microarray experiment from conception to interpretation. It begins with foundational issues such as ensuring the quality and integrity of the data and assessing the validity of the statistical models employed, then moves on to cover critical aspects of designing a microarray experiment.  The book includes discussions of power and sample size, where only very recently have developments allowed such calculations in a high dimensional context, followed by several chapters covering the analysis of microarray data. The amount of space devoted to this topic reflects both the variety of topics and the effort investigators have devoted to developing new methodologies. In closing, the book explores the intellectual frontier – interpretation of microarray data. It discusses new methods for facilitating and affecting formalization of the interpretation process and the movement to make large high dimensional datasets public for further analysis, and methods for doing so.

There is no question that this field will continue to advance rapidly and some of the specific methodologies discussed in this book will be replaced by new advances. Nevertheless, the field is now at a point where a foundation of key categories of methods has been laid out and begun to settle. Although the details may change, the majority of the principles described in this book and the foundational categories it contains will stand the test of time, making the book a touchstone for researchers in this field. ... Read more

Customer Reviews (1)

Exquisite coverage of existing & developing methodologies
An expansive tour of existing statistical methodologies used in microarray data analysis from contributed experts. What it does is deeply explore what people are using nowadays, cites references in each chapter beautifully, and gives the reader a solid footing as to the pros and cons of each technique presented. Each chapter delves deep enough, and by citing references extensively, one can go seek further detail from the source.

IMHO, this is probably one of the most professionally done books out there. By that I mean there is no fluff, just high quality content across the board. The intended audience is those having some computational background, particularly in statistics. However, each chapter begins with an introductory paragraph serving as a review so that anyone could pretty much gather what is going to be discussed.

A really nice feature of this compilation is that not only does it provide insight into the current methods, it outlines where further developments are needed and how they may help in filling in the gaps.With so many developments having been made in microarray data analysis recently, its nice to know that this book exists to help one gain a solid foundation on how to proceed with some sort of clarity. A five star rating for this one hands down. :) ... Read more

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Illustrates the important applications of biostatistical methods in the solution of common clinical problems...a comprehensive exam at the end of the book simulates the new format of the NBME Part 1 Exam. ... Read more

Customer Reviews (2)

Clinical Epidemiology and Biostatistics
book combines concepts of Epidemiology and biostatistics. It makes easy to understand how epidemiology is interlinked with biostatistics because in a clinical trial both are needed. I like this book because the language is easy to interpret. It is very useful for those who have difficulty in understanding the concepts of biostatistics. The best part of the book is that the text is explained in reference to clinical research, which makes life easier for medical students and doctors. A lot of examples are given within the text to make the text easy to understand. After each chapter a comprehensive test is given.

To cut the long story short, This book is one of the best for those who have difficulty in understanding Biostatistics.

Clinical Epidemiology and Biostatistics
Many books are available on epidemiology and biostatistics. This book combines concepts of Epidemiology and biostatistics. It makes easy to understand how epidemiology is interlinked with biostatistics because in a clinical trial both are needed. I like this book because the language is easy to interpret. It is very useful for those who have difficulty in understanding the concepts of biostatistics. The best part of the book is that the text is explained in reference to clinical research, which makes life easier for medical students and doctors. A lot of examples are given within the text to make the text easy to understand. After each chapter a comprehensive test is given.

To cut the long story short, This book is one of the best for those who have difficulty in understanding Biostatistics. ... Read more

Product Description
Managerial Epidemiology for Health Care Organizations provides readers with a thorough and comprehensive understanding of the application of epidemiological principles to the delivery of health care services and management of health care organizations. As health administration becomes evidence- and population-based, it becomes critical to understand the impact of disease on populations of people in a service area. This book also addresses the need of health organizations’ to demonstrate emergency preparedness and respond to bioterrorism threats. A follow-up to the standard text in the field, this book introduces core epidemiology principles and clearly illustrates their essential applications in planning, evaluating, and managing health care for populations. This book demonstrates how health care executives can incorporate the practice of epidemiology into their various management functions and is rich with current examples, concepts, and case studies that reinforce the essential theories, methods, and applications of managerial epidemiology. ... Read more

Customer Reviews (3)

Very recommended book
It is a very good book for students and professionnals. I recommend it to every one seeking good knowledge on applied epidemiology to the management of healthcare organization.

I needed the book for school.It serves the purpose
There is quite a bit of highlighting but I'm just using a different color.The book itself is in great condition.

Easy to read but multiple erros
My students find the book easy to read and understand but are frustrated by the multiple errors and missing data in Chapter five data examples and end of chapter questions. ... Read more

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Helping you become a creative, logical thinker and skillful "simulator," Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies provides broad coverage of the entire drug development process, from drug discovery to preclinical and clinical trial aspects to commercialization. It presents the theories and methods needed to carry out computer simulations efficiently, covers both descriptive and pseudocode algorithms that provide the basis for implementation of the simulation methods, and illustrates real-world problems through case studies.

The text first emphasizes the importance of analogy and simulation using examples from a variety of areas, before introducing general sampling methods and the different stages of drug development. It then focuses on simulation approaches based on game theory and the Markov decision process, simulations in classical and adaptive trials, and various challenges in clinical trial management and execution. The author goes on to cover prescription drug marketing strategies and brand planning, molecular design and simulation, computational systems biology and biological pathway simulation with Petri nets, and physiologically based pharmacokinetic modeling and pharmacodynamic models. The final chapter explores Monte Carlo computing techniques for statistical inference.

This book offers a systematic treatment of computer simulation in drug development. It not only deals with the principles and methods of Monte Carlo simulation, but also the applications in drug development, such as statistical trial monitoring, prescription drug marketing, and molecular docking.

Product Description
This book is an expanded version of the Kahn's widely used text, An Introduction to Epidemiologic Methods (Oxford, 1983).It provides clear insight into the basic statistical tools used in epidemiology and is written so that those without advanced statistical training can comprehend the ideas underlying the analytical techniques.The authors emphasize the extent to which similar results are obtained from different methods, both simple and complex. To this edition they have added a new chapter on "Comparison of Numerical Results for Various Methods of Adjustment" and also one on "The Primacy of Data Collection."New topics include the Kaplan-Meier product-limit method and the Cox proportional hazards model for analysis of time-related outcomes.An appendix of data from the Framingham Heart Study is used to illustrate the application of various analytical methods to an identical set of real data and provides source material for student exercises. The text has been updated throughout. ... Read more

Customer Reviews (3)

good
for medical students or those which start to study epidemiology and public health professionals, very good simple book

nice introductory level text
The authors are reputable epidemiologists who have written a concise and clear elementary treatment of the statistical methods that are used in epidemiology.The book is very practical and includes some major real data sets.The authors spend a lot of time covering random sampling, the relative risk and the odds ratio and provide enough exercises at the end of the chapters to engage the students.This is a great text for a first course or for self-study.It also is a fine reference book for statisticians and practitioners.

Kahn and Sempos
What we like.Comprehensive, concise, and clear.Fills the VOID left byother epidemiology analysis texts and the statistics not calculated by SPSSand SAS.Our constant companion in each epidemiology research task. Whatwe do not like.More information on regression analysis in the nextedition please. ... Read more

Product Description

The concept of frailty offers a convenient way to introduce unobserved heterogeneity and associations into models for survival data. In its simplest form, frailty is an unobserved random proportionality factor that modifies the hazard function of an individual or a group of related individuals. Frailty Models in Survival Analysis presents a comprehensive overview of the fundamental approaches in the area of frailty models.

The book extensively explores how univariate frailty models can represent unobserved heterogeneity. It also emphasizes correlated frailty models as extensions of univariate and shared frailty models. The author analyzes similarities and differences between frailty and copula models; discusses problems related to frailty models, such as tests for homogeneity; and describes parametric and semiparametric models using both frequentist and Bayesian approaches. He also shows how to apply the models to real data using the statistical packages of R, SAS, and Stata. The appendix provides the technical mathematical results used throughout.

Written in nontechnical terms accessible to nonspecialists, this book explains the basic ideas in frailty modeling and statistical techniques, with a focus on real-world data application and interpretation of the results. By applying several models to the same data, it allows for the comparison of their advantages and limitations under varying model assumptions. The book also employs simulations to analyze the finite sample size performance of the models.

Product 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 (4)

great in describing the motivation of multilevel analysis
This book accomplishes its goal. It does not seek to describe the statistical details of multilevel analysis (hierarchical models/mixed models). It clearly motivates when these analyses should be used. The author cites several other texts that go over details, but believes that the literature lacks a descriptive overview of these methods. The book served this purpose for me.

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

Product Description
A unique and invaluable reference resource for those working in survival analysis.

Survival analysis is concerned with studying the time between entry to a study and a subsequent event. Originally the analysis was concerned with time from treatment until death, hence the name, but survival analysis is applicable to many areas in addition to mortality, such as recidivism or the efficacy of drugs. The techniques can also be used in engineering and quality control (e.g. how long is a particular component likely to last?).

Arranged in an A-Z format, Survival and Event History Analysis edited by Niels Keiding and Per Kragh Andersen contains 96 articles written by over 60 distinguished authors. The articles are taken from the Encyclopedia of Biostatistics, 2nd Edition.

This book gives the reader a thorough grounding in the subject area and the extensive references at the end of each article provide a comprehensive source of information for further information in more depth. ... Read more

Product Description
The Encyclopedia of Biostatistics is an outstanding achievement in scientific publishing comprising over 1200 articles written by more than 800 contributors. A truly international work, it includes extensive coverage of statistical issues pertinent to life scientists, healthcare professionals and practising statisticians.
Entries cover everything from basic statistical concepts, to practical issues arising in research or medical administration, through to the most advanced methods and theoretical developments. Each contribution has been carefully selected and reviewed through the collaborative efforts of the Editors-in-Chief, Peter Armitage (Oxford, UK) and Ted Colton (Boston, USA), with further assistance from an editorial board that spans Europe, North America, Australia, Asia and the Middle East.
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. The Encyclopedia offers extensive coverage of the key subject areas:
? Clinical Trials
? Vital and Health Statistics
? Epidemiology
? Health Services Research
? Human Genetics
? Laboratory and Basic Science Research
? Modelling of diseases and Human Biologic Phenomena
? Speciality-specific Statistics
? Statistical Models
? Categorical Data Analysis
? Survival Analysis
? Longitudinal Data Analysis and Time Series
? Multivariate Analysis
? Computation
? Statistical Theory and methods
? Design of Experiments and Sample Surveys
? Institutional and Historical Accounts
The Encyclopedia of Biostatistics Website includes comprehensive information on this outstanding work. ... Read more

Product Description
Featuring articles from the prestigious Encyclopedia of Biostatistics, many of which have been revised and updated to include recent developments, the Encyclopedia of Epidemiologic Methods also includes newly commissioned articles reflecting the latest thinking in

• Cancer Registries
  
• Birth Defect Registries
  
• Meta Analysis of Epidemiologic Studies
  
• Epidemiology Overview
  
• Sample Size
  
• Sex Ratio at Birth
  
• Software Design and Analysis

Featuring contributions from leading experts in academia, government and industry, the Encyclopedia of Epidemiologic Methods has been designed to complement existing texts on the subject by providing further extensive, up-to-date coverage of specialised topics and by introducing the reader to the research literature.

Offering a wealth of information in a single resource, the Encyclopedia of Epidemiologic Methods

• Offers an excellent introduction to a vast array of specialised topics
  
• Includes in-depth coverage of the statistical underpinnings of contemporary epidemiologic methods
  
• Provides concise definitions and introductions to numerous concepts found in the current literature
  
• Uses extensive cross-references, helping to facilitate further research, and enabling the reader to locate definitions and related concepts

In addition to featuring extensive articles in the areas of descriptive and analytic epidemiology, the Encyclopedia also provides the reader with articles on case-control design and offers substantial coverage of allied statistical methods.

From the Reviews….
"a selection of excellent articles"
(Short Book Reviews, December 2001)

"The articles were written by experts...hence the quality of entries is quite good. The editors have done an excellent job..."
(Journal of the American Statistical Association, December 2001)

"There is no doubt that this…is an invaluable tool for researchers involved in medical and public health research as it offers an excellent springboard for acquiring and strengthening practical and methodological tools."
(Short Book Reviews, Vol. 21, No. 3, December 2001)

"...illuminating and comprehensive and often of extremely high quality..."
(Biometrics, September 2002)

... Read more

Customer Reviews (4)

good encyclopedia on an important topic
For a biostatistician at a pharmaceutical company who needs to combine clinical trial data with information in the literature from case-control and other non-randomized data, understanding of the latest epidemiologic methods is essential. In this reference source Mitch Gail and Jacques Benichou provide all the important abbreviations and acronyms and 201 articles listed alphabetical by title along with author and subject indices at the end of the volume. Each article has its own list of references to the relevant literature. The list of contributors is over 140 including many very famous biostatisticians from around the world.
It is a single volume that is 978 pages long and although it is expensive for an individual to purchase, it merits having in a biostatistics library or any technical library where medical research is conducted.

Here is a selected list of topics: Age-Period-Cohort Analysis, Berkson's Fallacy, Bias, Bias in Obersvational Studies, Case-Cohort Study, Case-Control Study, Causation, Cornfield's Inequality, Cox Regression Model, Death Indexes, Demography, Dose-Response, Epidemiology as Legal Evidence, Frequency Matching,Hawthorne Effect, Kappa, Length Bias, Life Table, Logistic Regression, Meta-Analysis in Epidemiology, Occupational Mortality, Odds Ratio, Prevalence, Propensity Score,Retrospective Study, Selection Bias, Simpson's Paradox, and Validation Study.

Among the contributors are Peter Armitage, Norman Breslow, Ray Carroll, Ted Colton, Mitch Gail, Joe Gastwirth, David Hosmer, Gary Koch, Stanley Lemeshow, Rod Little, Ross Prentice, George Seber, Butch Tsiatis, and Michael Vaeth. The work is very much up-to-date as it was published in 2000. It includes updates of many articles that were in the highly praised six volume Encyclopedia of Biostatistics. It concentrates on those articles that focus on topics important to epidemiology. It also includes several articles written specifically for this volume.

Mathematical & Biostatistical Epidemiological Methods
This is a very good textbook and reference for those seeking to model and understand epidemiology techniques.Calculus and probability theory are introduced at a basic level and the book progresses onto advanced concepts of statistical modeling.It has an A to Z format which makes it useful for looking up topics easily.The book starts out with fundamental techniques but explores complicated topics in greater detail toward the end of the single volume.I really like it as an MPH Student interested in epidemiology and plan on using it alot more in my career.Five Hundred dollars is alot, but probably worth it.This book is possibly not an absolute necessity, but I am glad I purchased it when I did, in the first year of the MPH Program.

Young scientist
This is a very valuable book, helping to be familiar with epidemiological methods. This will alllow you to use right epidemiological methods in preparing scientistic work. Thank for authors.

Young scientist
This is a very valuable book, helping to be familiar with epidemiological methods. This will alllow you to use right epidemiological methods in preparing scientistic work. Thank for authors. ... Read more

Product Description

This book covers a wide range of recent statistical methods that are of interest to scientists in biostatistics as well as in other related fields such as chemometrics, environmetrics and geophysics. The contributed papers, from internationally recognized researchers, present various statistical methodologies together with a selected scope of their main mathematical properties and their application in a real case study.

Product Description
Biostatistics for Epidemiologists is a unique book that provides a collection of methods that can be used to analyze data in most epidemiological studies. It examines the theoretical background of the methods described and discusses general principles that apply to the analysis of epidemiological data. Specific topics addressed include statistical interference in epidemiological research, important methods used for analyzing epidemiological data, multivariate models, dose-response analysis, analysis of the interaction between causes of disease, meta-analysis, and computer programs. Biostatistics for Epidemiologists will be a useful guide for all epidemiologists and public health professionals who rely on biostatistical data in their work. ... Read more

Product Description

Already popular in the analysis of medical device trials, adaptive Bayesian designs are increasingly being used in drug development for a wide variety of diseases and conditions, from Alzheimer’s disease and multiple sclerosis to obesity, diabetes, hepatitis C, and HIV. Written by leading pioneers of Bayesian clinical trial designs, Bayesian Adaptive Methods for Clinical Trials explores the growing role of Bayesian thinking in the rapidly changing world of clinical trial analysis.

The book first summarizes the current state of clinical trial design and analysis and introduces the main ideas and potential benefits of a Bayesian alternative. It then gives an overview of basic Bayesian methodological and computational tools needed for Bayesian clinical trials. With a focus on Bayesian designs that achieve good power and Type I error, the next chapters present Bayesian tools useful in early (Phase I) and middle (Phase II) clinical trials as well as two recent Bayesian adaptive Phase II studies: the BATTLE and ISPY-2 trials. In the following chapter on late (Phase III) studies, the authors emphasize modern adaptive methods and seamless Phase II–III trials for maximizing information usage and minimizing trial duration. They also describe a case study of a recently approved medical device to treat atrial fibrillation. The concluding chapter covers key special topics, such as the proper use of historical data, equivalence studies, and subgroup analysis.

For readers involved in clinical trials research, this book significantly updates and expands their statistical toolkits. The authors provide many detailed examples drawing on real data sets. The R and WinBUGS codes used throughout are available on supporting websites.

Product Description
Univ. of Wisconsin, Madison. Explores types of variables, random sampling, probability, measures of central tendency, and hypothesis testing. Covers the use of statistical tests for correctly interpreting research results. Includes almost 500 equations, tables, drawings, and references. For pharmacists and students. ... Read more

Customer Reviews (1)

Adventures in Pharmaceutical Statistics
As the cover of the text would indicate, James DeMuth's "Basic Statistics and Pharmaceutical Statistical Applications" sends the reader on a roller coaster ride through the intriguing world of statitics. In this edition, Dr. Demuth astutely details the methodology necessary tosummarize data and make informed decisions about observed outcomes.Moreimportantly though, he provides concrete examples which enable the readerto effectively deploy the information in their day-to-day lives.Thisedition, undoubtedly the first of many more to come, should prove to be aninvaluable resource for students, practicing pharmacists and industrialscientists alike. ... Read more