Biostatistics

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Big Savings on New and Essential Books in

Biostatistics from CRC Press

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Contents Clinical Trials & Pharmaceutical Research ............3 Biostatistics Theory & Methods ............................7 Survival Analysis..................................................10 Computational Biostatistics ................................12 Epidemiology......................................................14 Page 3

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Medical Diagnostics............................................16 Statistics for Life Sciences....................................17 Statistical Genetics ..............................................18

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Clinical Trials & Pharmaceutical Research New!

New!

Randomised ResponseAdaptive Designs in Clinical Trials

Benefit-Risk Assessment in Pharmaceutical Research and Development

Anthony C. Atkinson and Atanu Biswas This book presents methods for the randomized allocation of treatments to patients in sequential clinical trials. Emphasizing the practical application of clinical trial designs, the book is designed for medical and applied statisticians, clinicians, and statisticians in training. The authors compare various designs of clinical trials, include real examples of clinical trials, and present simulations of many procedures for small to moderate-sized samples. They also use results from the optimum design of experiments to create powerful and flexible adaptive designs.

Catalog no. C6935, December 2013, 339 pp.

ISBN: 978-1-58488-693-8, $89.95 / £57.99 Also available as an eBook

Randomized Phase II Cancer Clinical Trials Sin-Ho Jung Duke University, Durham, North Carolina, USA

“… an excellent book covering various practical phase II designs with their associated statistical methods for cancer clinical trials. It is an asset to statistical professionals who work in industry or academia and would like to learn more about or improve their understanding of phase II trial design and methods for cancer clinical trials. The book can also be used as a textbook for graduate students with a statistical major.”

—Steven Sun, Janssen Research Development, New Jersey, USA

Catalog no. K13295, May 2013, 244 pp.

ISBN: 978-1-4398-7185-0, $89.95 / £57.99 Also available as an eBook

Edited by

Andreas Sashegyi, James Felli, and Rebecca Noel Eli Lilly and Company, Indianapolis, Indiana, USA

Bringing together the expertise of 15 contributors from academia and the industry, this book offers an easy-to-read guide to the various facets of benefit-risk assessment in the major stages of pharmaceutical R&D, from early clinical development to late-stage development to regulatory review to post-launch assessment. Suitable for those in both technical and managerial roles, it enables readers to communicate more effectively across their development chain as well as rationally and thoughtfully embed benefit-risk assessment into their R&D processes.

Catalog no. K13085, November 2013, 220 pp.

ISBN: 978-1-4398-6794-5, $89.95 / £57.99 Also available as an eBook

New!

Clinical and Statistical Considerations in Personalized Medicine Edited by

Claudio Carini and Sandeep M Menon Pfizer, Cambridge, Massachusetts, USA

Mark Chang AMAG Pharmaceuticals, Inc, Lexington, Massachusetts, USA

This book is one of the first to incorporate both the clinical and statistical aspects of biomarkers in the personalized medicine paradigm. Leading clinicians, biostatisticians, regulators, commercial professionals, and researchers address the opportunities and challenges in successfully applying biomarkers in drug discovery and preclinical and clinical development. They cover a wide spectrum of personalized medicine-related topics, including epigenetics, adaptive designs, statistical methods, regulatory issues, and more.

Catalog no. K20653, April 2014, 358 pp.

ISBN: 978-1-4665-9386-2, $89.95 / £57.99 Also available as an eBook

For more information and complete contents, visit www.crcpress.com

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Clinical Trials & Pharmaceutical Research Biosimilars

New!

PatientReported Outcomes

Design and Analysis of Follow-on Biologics

Measurement, Implementation and Interpretation Joseph C. Cappelleri, Kelly H. Zou, Andrew G. Bushmakin, Jose Ma. J. Alvir, Demissie Alemayehu, and Tara Symonds Advancing the development, validation, and use of PRO measures, this book helps readers develop and enrich their understanding of PRO methodology, particularly from a quantitative perspective. It provides an up-to-date volume on conceptual and analytical issues of PRO measures. The authors include many real-life applications and implement a wealth of simulated datasets to illustrate concepts. Most chapters contain SAS code and output that demonstrate the methodology.

Catalog no. K13411, December 2013, 351 pp.

ISBN: 978-1-4398-7367-0, $99.95 / £63.99 Also available as an eBook

Theory of Drug Development Eric B. Holmgren This book focuses on the efficient development of drugs and the quantification of evidence in drug development.

It presents a formal quantitative framework for understanding drug development that goes beyond simply describing the properties of the statistics in individual studies. Examining the drug development process from the perspectives of both drug companies and regulatory agencies, the author provides a rationale for underpowered phase 2 trials based on the notion of efficiency and develops a framework for evaluating the strength of evidence generated by clinical trials.

Catalog no. K14671, October 2013, 261 pp.

ISBN: 978-1-4665-0746-3, $89.95 / £57.99 Also available as an eBook

Shein-Chung Chow Duke University School of Medicine, Durham, North Carolina, USA

Written by a top biostatistics researcher, this is the first book entirely devoted to the statistical design and analysis of biosimilarity and interchangeability of biosimilar products. It includes comparability tests of important quality attributes at critical stages of the manufacturing processes of biologic products. The book focuses on the scientific factors and practical issues related to the design and analysis of biosimilar studies. It covers most of the statistical questions encountered in various study designs at different stages of research and development of biological products.

Catalog no. K16860, July 2013, 444 pp.

ISBN: 978-1-4665-7969-9, $89.95 / £57.99 Also available as an eBook

Adaptive Design Methods in Clinical Trials Second Edition Shein-Chung Chow Duke University School of Medicine, Durham, North Carolina, USA

Mark Chang AMAG Pharmaceuticals, Inc, Lexington, Massachusetts, USA

“In this second edition, the authors update two chapters on protocol amendment and clinical trial simulation … and add five new chapters. … an excellent book … very useful to graduate students … . The book is very well written and a joy to read. I think it would be a critical addition to the bookshelf for statisticians involved in adaptive design and analysis in clinical trials.”

—Hongfei Guo, Journal of the American Statistical Association, December 2013

Catalog no. K11837, December 2011, 374 pp.

ISBN: 978-1-4398-3987-4, $93.95 / £62.99 Also available as an eBook

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Clinical Trials & Pharmaceutical Research Design and Analysis of Non-Inferiority Trials Mark D. Rothmann, Brian L. Wiens, and Ivan S.F. Chan “It is refreshing to see FDA and industry perspectives blended thoughtfully, as in this book. … Written clearly and concisely, the book is a pleasure to read. Although there are some technical discussions intended for statisticians, most of the book is readily accessible to medical researchers with little statistical training. We recommend the book to anyone interested in NI trials—statisticians and nonstatisticians alike.”

—Zhiwei Zhang and Lei Nie, Journal of the American Statistical Association, March 2014

Catalog no. C8040, July 2011, 454 pp.

ISBN: 978-1-58488-804-8, $98.95 / £62.99 Also available as an eBook

Dose Finding by the Continual Reassessment Method Ying Kuen Cheung Columbia University, New York, New York, USA

This book presents the continual reassessment method (CRM) as a tool for dose-finding studies. With a focus on the implementation and practice of the CRM and its variations, it explains how the CRM may be calibrated and extended to suit common clinical settings.

The book includes examples of real clinical trials data to illustrate the calibration techniques and shows how R can be used to carry out the techniques. It reviews the literature, related methodology, and theoretical properties of the CRM. It also explores alternatives for situations where the CRM fails.

Catalog no. C9151, March 2011, 200 pp.

ISBN: 978-1-4200-9151-9, $87.95 / £55.99 Also available as an eBook

Controversial Statistical Issues in Clinical Trials

Clinical Trial Data Analysis Using R

Shein-Chung Chow

University of Rochester Medical Center, New York, USA

Duke University School of Medicine, Durham, North Carolina, USA

“… it is very valuable that the book calls the reader’s attention to the numerous problems, which are relevant every day, and I recommend to make this book available to personnel in all biometrical university departments, CROs, and operating departments in the pharmaceutical industry to enable them to cope with the most important controversial aspects in planning and execution of clinical studies.”

—Rainer Muche, ISCB News, December 2013

Catalog no. K12247, June 2011, 611 pp.

ISBN: 978-1-4398-4961-3, $104.95 / £69.99 Also available as an eBook

Din Chen Karl E. Peace Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, USA

“… a good primer to the most commonly used methods and their utilisation in R, as well as extensive lists of references to more detailed considerations. … this book can certainly stand on any biostatisticians’ shelf as a useful text. For the seasoned methodologist, it provides a helpful introduction to the R environment. For R proponents, it delivers a simple overview of the established clinical biostatistics methodology.”

—Michael Grayling, ISCB News, December 2013

Catalog no. K11861, December 2010, 387 pp.

ISBN: 978-1-4398-4020-7, $98.95 / £62.99 Also available as an eBook

For more information and complete contents, visit www.crcpress.com

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Clinical Trials & Pharmaceutical Research Bayesian Adaptive Methods for Clinical Trials

Handbook of Statistics in Clinical Oncology

Scott M. Berry, Bradley P. Carlin, J. Jack Lee, and Peter Müller

Edited by

“The authors, while clearly advocating the use of Bayesian approaches, nevertheless take a very pragmatic approach to the issue. They argue for Bayesian methods that demonstrate good frequentist properties and that are practical to use. This is a refreshing change from some other books and papers … I found this book to be well written and interesting. … a useful resource for statisticians and nonstatisticians alike interested in adaptive clinical trials from a Bayesian perspective.”

Antje Hoering

Third Edition John Crowley Cancer Research and Biostatistics, Seattle, Washington, USA

—Biometrics, 67, September 2011

Catalog no. K11217, July 2010, 323 pp.

ISBN: 978-1-4398-2548-8, $104.95 / £65.99 Also available as an eBook

Cancer Research and Biostatistics, University of Washington, and Fred Hutchinson Cancer Research Center, Seattle, USA

“A strength of the handbook is the large number of examples … . Each chapter provides details of new developments in the specific methodology and provides a comprehensive list of references … The book contains a wealth of information about a wide range of statistical methodologies, some of which are not limited to clinical trials. … a valuable update to a resource that covers a comprehensive range of topics related to the design, analysis, and interpretation of clinical trials in cancer research.”

—Peter Baade, Australian & New Zealand Journal of Statistics, 2013

Catalog no. K12872, March 2012, 657 pp.

ISBN: 978-1-4398-6200-1, $125.95 / £81.00 Also available as an eBook

Clinical Trials in Oncology Third Edition Stephanie Green, Jacqueline Benedetti, Angela Smith, and John Crowley This new edition of a bestseller provides a nontechnical review of methods and issues related to clinical trials. The authors emphasize the importance of proper study design, analysis, and data management and identify the pitfalls inherent in these processes. The book has been restructured with separate chapters and expanded discussions on general clinical trial issues and issues specific to Phases I, II, and III. New sections cover innovations in Phase I designs, randomized Phase II designs, and overcoming the challenges of array data.

Catalog no. K10744, May 2012, 264 pp.

ISBN: 978-1-4398-1448-2, $104.95 / £66.99 Also available as an eBook

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Monte Carlo Simulation for the Pharmaceutical Industry Concepts, Algorithms, and Case Studies Mark Chang AMAG Pharmaceuticals, Inc, Lexington, Massachusetts, USA

“… the ability of the author to condense such a broad array of topics and to present them in a cohesive manner is quite impressive … Many statisticians working in the pharmaceutical industry will benefit from having access to a copy of this book. Some statisticians working outside the industry may also benefit from having a copy, particularly those working in areas overlapping with the pharmaceutical industry, such as clinical science and health economics.”

—Ian C. Marschner, Australian & New Zealand Journal of Statistics, 2011

Catalog no. K11621, September 2010, 564 pp.

ISBN: 978-1-4398-3592-0, $98.95 / £62.99 Also available as an eBook

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Biostatistics Theory & Methods Coming soon!

Age-PeriodCohort Models Approaches and Analyses with Aggregate Data Robert M. O’Brien University of Oregon, Eugene, USA

One of the first to do so, this book integrates the major approaches to APC analysis for aggregate-level data, such as uniform crime reports, vital statistics, and census data. It connects the traditional methods of constrained estimation, estimation using cohort (or age or period) characteristics, estimable functions, the overidentification approach of Winship and Harding, variance decomposition, and a sufficient condition for age, period, or cohort effects.

Catalog no. K15175, July 2014, c. 208 pp.

ISBN: 978-1-4665-5153-4, $79.95 / £49.99 Also available as an eBook

Age-PeriodCohort Analysis New Models, Methods, and Empirical Applications Yang Yang University of North Carolina, Chapel Hill, USA

Kenneth C. Land Duke University, Durham, North Carolina, USA

This book explores the ways in which statistical models, methods, and research designs can be used to open new possibilities for APC analysis. Within a single, consistent HAPC-GLMM statistical modeling framework, the authors synthesize APC models and methods for three research designs. They show how the empirical application of the models to various problems leads to many fascinating findings on how outcome variables develop along the age, period, and cohort dimensions. Computational codes are available online.

Statistical Methods for Handling Incomplete Data Jae Kwang Kim and Jun Shao Along with many examples, this text covers up-to-date statistical theories and computational methods for analyzing incomplete data. It presents a thorough treatment of statistical theories of likelihood-based inference with missing data. It also discusses numerous computational techniques and theories on imputation and extensively covers methods involving propensity score weighting, nonignorable missing data, longitudinal missing data, survey sampling, and statistical matching. Some of the research ideas introduced can be developed further for specific applications.

Catalog no. K12249, July 2013, 223 pp.

ISBN: 978-1-4398-4963-7, $89.95 / £57.99 Also available as an eBook

Flexible Imputation of Missing Data Stef van Buuren TNO Quality of Life, Leiden, The Netherlands

“This book would be well suited as a textbook, especially at the graduate level, possibly for biostatisticians, epidemiologists, or applied scientists and users of statistical methodology. … a very enjoyable read, and—at least in my opinion—it is a book that belongs on everyone’s shelf as it does open one’s eyes to a problem that has surrounded us (and that many of us have ignored!) for a very long time.”

—Wolfgang S. Jank, Journal of the American Statistical Association, June 2013

Catalog no. K13103, March 2012, 342 pp.

ISBN: 978-1-4398-6824-9, $93.95 / £59.99 Also available as an eBook

Catalog no. K14675, February 2013, 352 pp.

ISBN: 978-1-4665-0752-4, $79.95 / £49.99 Also available as an eBook

For more information and complete contents, visit www.crcpress.com

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Biostatistics Theory & Methods Analysis of Mixed Data Methods & Applications Edited by

Alexander R. de Leon University of Calgary, Alberta, Canada

Robert G. Newcombe

Keumhee Carrière Chough

Cardiff University, Wales

University of Alberta, Edmonton, Canada

This book offers a complete introduction to and summary of the fundamental advances in the field. It presents modern methods and case studies throughout the book to illustrate interesting applications from economics, medicine and health, marketing, and genetics. All chapters include illustrative examples, many drawn from real-life case studies. Ample crossreferences between chapters enable readers to connect the book’s various topics and research strands and to facilitate self-study.

Catalog no. K13979, January 2013, 262 pp.

ISBN: 978-1-4398-8471-3, $89.95 / £57.99 Also available as an eBook

Statistical Analysis of Human Growth and Development Yin Bun Cheung Designed for nonstatisticians and statisticians new to the analysis of growth and development data, this book is an accessible and practical guide to a wide range of basic and advanced statistical methods that are useful for studying human growth and development. It collects methods scattered throughout the literature and explains how to use them to solve common research problems. It also discusses how well a method addresses a specific scientific question and how to interpret and present the analytic results. Stata codes are available on the book’s CRC Press web page.

Catalog no. K13277, October 2013, 378 pp.

ISBN: 978-1-4398-7154-6, $99.95 / £63.99 Also available as an eBook

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Confidence Intervals for Proportions and Related Measures of Effect Size “…this is a fantastic book, and I would recommend it highly, especially for medical researchers and statisticians in the medical field.”

—Vance W. Berger, Journal of Biopharmaceutical Statistics

“This is an interesting and well-written book … the examples alone comprise a valuable teaching resource. … there will be something of value, to think about or enjoy, for almost all readers who like statistics in general or data analysis in particular. It is a pleasure to recommend it.”

—Bruce Brown, Australian & New Zealand Journal of Statistics, 2014

Catalog no. K10649, August 2012, 468 pp.

ISBN: 978-1-4398-1278-5, $93.95 / £59.99 Also available as an eBook

Applied Categorical and Count Data Analysis Wan Tang, Hua He, and Xin M. Tu University of Rochester, New York, USA

“The combination of more advanced and mathematical explanations, newer topics, and sample code from all major software platforms makes this book a valuable addition to the literature on categorical data analysis.”

—Russell L. Zaretzki, Journal of the American Statistical Association, September 2013

This self-contained text explains how to perform the statistical analysis of discrete data. R, SAS, SPSS, and Stata programming codes are provided for all the examples, enabling readers to immediately experiment with the data in the examples.

Catalog no. K10311, June 2012, 384 pp.

ISBN: 978-1-4398-0624-1, $93.95 / £59.99 Also available as an eBook

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Biostatistics Theory & Methods Optimal Design for Nonlinear Response Models Valerii V. Fedorov Quintiles, Durham, North Carolina, USA

Sergei L. Leonov AstraZeneca, Wilmington, Delaware, USA

This book discusses the theory and applications of model-based experimental design with a strong emphasis on biopharmaceutical studies. While the focus is on nonlinear models, the book begins with an explanation of the key ideas, using linear models as examples. Applying the linearization in the parameter space, it then covers nonlinear models and locally optimal designs as well as minimax, optimal on average, and Bayesian designs. The authors also discuss adaptive designs, focusing on procedures with noninformative stopping.

Catalog no. K11140, July 2013, 402 pp.

ISBN: 978-1-4398-2151-0, $89.95 / £57.99 Also available as an eBook

Applied MetaAnalysis with R Ding-Geng (Din) Chen University of Rochester, New York, USA

Karl E. Peace Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, USA

This book provides detailed, step-by-step explanations of the implementation of meta-analysis methods using R. Each chapter gives examples of real studies compiled from the literature. After presenting the data and necessary background for understanding the applications, various methods for analyzing meta-data are introduced. The authors then develop analysis code using the appropriate R packages and functions.

This systematic approach helps readers thoroughly understand the analysis methods and R implementation, enabling them to use R and the methods to analyze their own meta-data.

Catalog no. K14600, May 2013, 342 pp.

ISBN: 978-1-4665-0599-5, $89.95 / £57.99 Also available as an eBook

Regression Models as a Tool in Medical Research Werner Vach “The book can be a very helpful contribution especially for researchers in medical sciences when performing their statistical analyses and trying to interpret the results obtained. …”

—Tapio Nummi, International Statistical Review (2013), 81

Catalog no. K15111, November 2012, 495 pp.

ISBN: 978-1-4665-1748-6, $93.95 / £59.99 Also available as an eBook

Bayesian Methods in Health Economics Gianluca Baio “This book is apparently the first book devoted to Bayesian statistical methods in health economics … suitable for researchers and practitioners who want to learn and apply statistical methods to health economics. … ” —Man-Suk Oh, Biometrics, March 2014

Catalog no. K14236, November 2012, 243 pp.

ISBN: 978-1-4398-9555-9, $93.95 / £59.99 Also available as an eBook

Exercises and Solutions in Biostatistical Theory Lawrence Kupper, Brian Neelon, and Sean M. O’Brien “This book is a rich collection of class-tested material given in the form of exercises followed by their complete solutions.”

—Jordan Stoyanov, Journal of the Royal Statistical Society, Series A, February 2014

Catalog no. C7222, November 2010, 420 pp.

Soft Cover, ISBN: 978-1-58488-722-5 $57.95 / £26.99 Also available as an eBook

For more information and complete contents, visit www.crcpress.com

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Survival Analysis Handbook of Survival Analysis

IntervalCensored Timeto-Event Data

Edited by

Methods and Applications

John P. Klein, Hans C. van Houwelingen, Joseph G. Ibrahim, and Thomas H. Scheike With chapters written by leading researchers in the field, this handbook presents modern techniques and research problems in lifetime data analysis. It helps statisticians pick the best statistical method to analyze their survival data experiment. The book covers classical and Bayesian approaches. It gives a complete overview of the current status of survival analysis and should inspire further research in the field.

Catalog no. K15384, July 2013, 656 pp.

ISBN: 978-1-4665-5566-2, $99.95 / £63.99 Also available as an eBook

Ding-Geng (Din) Chen, Jianguo Sun, and Karl E. Peace This practical guide covers developments in the analysis and modeling of interval-censored time-to-event data. Top researchers from academia, biopharmaceutical industries, and government agencies show how statistical methods are used in biopharmaceutical and public health applications. The book presents data from actual clinical trials and biomedical research, including breast cancer and HIV data sets. It also offers easy access to computational methods and R software packages.

Catalog no. K14515, July 2012, 433 pp.

ISBN: 978-1-4665-0425-7, $104.95 / £66.99 Also available as an eBook

Joint Models for Longitudinal and Time-toEvent Data

Survival Analysis in Medicine and Genetics Jialiang Li National University of Singapore

Shuangge Ma Yale University, New Haven, Connecticut, USA

“This book provides a new outlook on survival analysis methods by emphasizing the application of the statistical methods for biological and genetic problems. … this book covers several important and specific topics, which have been rarely covered in other conventional survival textbooks. Throughout this book, many advanced statistical methods are well specified so that biostatisticians and researchers in medicine and genetics can easily understand and apply these methods to complicated survival data with high-dimensional covariates.”

—Seungyeoun Lee, Biometrics, March 2014

Catalog no. K14175, June 2013, 381 pp.

ISBN: 978-1-4398-9311-1, $99.95 / £63.99 Also available as an eBook

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Edited by

With Applications in R Dimitris Rizopoulos Erasmus University Medical Center, Rotterdam, Netherlands

“The book is well written in a matter-of-fact style that makes even unfamiliar readers understand the concept of joint models and, furthermore, provides them with a guide for getting started with their own analysis. … a handy guide for anyone with a need to analyze survival data in the presence of a timedependent covariate that is measured several times. … a satisfying book on joint models with a solid payout for fellow researchers.”

—Maral Saadati, Biometrical Journal, 55, 2013

Catalog no. K13371, June 2012, 275 pp.

ISBN: 978-1-4398-7286-4, $83.95 / £51.99 Also available as an eBook

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Survival Analysis Multivariate Survival Analysis and Competing Risks

Flexible Parametric Survival Analysis Using Stata

Martin J. Crowder

Beyond the Cox Model

Imperial College, University of London, UK

Suitable for graduate students and researchers in statistics and biostatistics as well as those in the medical field, epidemiology, and social sciences, this book introduces univariate survival analysis and extends it to the multivariate case. It also covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions, frailty models, parametric methods, multivariate data and distributions, copulas, continuous failure, parametric likelihood inference, and non- and semi-parametric methods.

Catalog no. K13489, April 2012, 417 pp.

ISBN: 978-1-4398-7521-6, $104.95 / £66.99 Also available as an eBook

Dynamic Prediction in Clinical Survival Analysis Hans C. van Houwelingen and Hein Putter Leiden University, The Netherlands

In the last 20 years, dynamic prediction models have been extensively used to monitor patient prognosis in survival analysis. Co-authored by one of the pioneers in the area, this book synthesizes these developments in a unified framework. It covers prognostic and dynamic prediction of survival using genomic data and time-dependent information. The text includes numerous examples using real data taken from the authors’ collaborative research. R programs are provided for implementing the methods.

Catalog no. K11593, November 2011, 250 pp.

ISBN: 978-1-4398-3533-3, $98.95 / £62.99 Also available as an eBook

Patrick Royston University College London and MRC Clinical Trials Unit, UK

Paul C. Lambert University of Leicester, UK

Through real-world case studies, this book shows how to use Stata to estimate a class of flexible parametric survival models. It discusses the modeling of timedependent and continuous covariates and looks at how relative survival can be used to measure mortality associated with a particular disease when the cause of death has not been recorded. The book describes simple quantification of differences between any two covariate patterns through calculation of timedependent hazard ratios, hazard differences, and survival differences.

Catalog no. N10372, August 2011, 339 pp.

Soft Cover, ISBN: 978-1-59718-079-5 $79.95 / £49.99

Frailty Models in Survival Analysis Andreas Wienke Martin-Luther-University Halle-Wittenberg, Germany

“Unlike previous books on this topic, this book has a special focus on correlated frailty models for bivariate survival data. … A strength of the book is the wide variety of real datasets used to illustrate models and methods. … a very useful reference for researchers in the area. … I would recommend this book to specialists for the breadth of its coverage of the literature and to other readers seeking to sample the flavor of ongoing methodological research in frailty models.”

—David Oakes, Biometrics, June 2012

Catalog no. C7388, July 2010, 312 pp.

ISBN: 978-1-4200-7388-1, $115.95 / £72.99 Also available as an eBook

For more information and complete contents, visit www.crcpress.com

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Computational Biostatistics Dynamic Documents with R and knitr

Reproducible Research with R and RStudio Christopher Gandrud

Yihui Xie Iowa State University, Ames, USA

“If you are looking to learn how to use knitr, this book is for you. There are a limited number of resources for learning knitr because the package is relatively new and the documentation produced by Xie is so good. … I think this book will continue to be the best resource about knitr … easy to understand … this is a great read and handy desk reference for the regular knitr user.”

—Journal of Statistical Software, January 2014

Catalog no. K21320, July 2013, 216 pp., Soft Cover ISBN: 978-1-4822-0353-0, $59.95 / £38.99

Hertie School of Governance, Berlin, Germany

Bringing together computational research tools in one accessible source, this book guides readers in creating dynamic and highly reproducible research. Whether an advanced user or just getting started with tools such as R and LaTeX, the book saves readers time searching for information and helps them successfully carry out computational research. It provides a practical reproducible research workflow for gathering and analyzing data as well as dynamically presenting results in print and on the web. Supplementary materials are available on the author’s website.

Catalog no. K16624, July 2013, 294 pp., Soft Cover ISBN: 978-1-4665-7284-3, $69.95 / £44.99

Implementing Reproducible Research

Applied Medical Statistics Using SAS

Edited by

Geoff Der

Victoria Stodden, Friedrich Leisch, and Roger D. Peng

University of Glasgow, Scotland

New!

Brian S. Everitt

This work covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result. Divided into three parts, the book discusses the tools, practices, and dissemination platforms for ensuring reproducibility in computational science.

Each part presents contributions from leaders who have developed software and other products that have advanced the field, including Sweave, open source software packages, and good programming practices. Chapters are fully reproducible with material available on the editors’ website.

Catalog no. K15945, April 2014, 448 pp.

ISBN: 978-1-4665-6159-5, $79.95 / £49.99 Also available as an eBook

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Professor Emeritus, King’s College, London, UK

“… a well-organized and thorough exploration of broad coverage in medical statistics. The book is an excellent reference of statistical methods with examples of medical data and SAS codes for statisticians or statistical analysts who are working in the medical/clinical area. It also can be a reference book for an introductory or intermediate graduate biostatistics course.”

—Jun Zhao, Journal of Biopharmaceutical Statistics, 24, 2014

Catalog no. K13087, October 2012, 559 pp.

ISBN: 978-1-4398-6797-6, $93.95 / £59.99 Also available as an eBook

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Computational Biostatistics Coming soon!

A Handbook of Statistical Graphics Using SAS Geoff Der University of Glasgow, UK

Brian S. Everitt Professor Emeritus, King’s College, London, UK

This handbook shows how to use SAS to create many different types of useful statistical graphics for exploring data and diagnosing fitted models. The book focuses on the relatively new SAS ODS graphics, including graphs that are produced routinely via ODS and more tailored graphics. Each chapter includes exercises and deals graphically with several sets of data from a wide variety of areas.

Catalog no. K20932, August 2014, c. 192 pp.

ISBN: 978-1-4665-9903-1, $69.95 / £44.99

New!

Displaying Time Series, Spatial, and Space-Time Data with R Oscar Perpinan Lamigueiro ETSIDI-UPM, Madrid, Spain

Focusing on the exploration of data with visual methods, this book presents methods and R code for producing high-quality graphics of time series, spatial, and space-time data. It illustrates how to display a dataset starting with an easy and direct approach and progressively adding improvements that involve more complexity. Practical examples using real-world datasets help readers understand how to apply the methods and code. The graphics, data, and R code are accessible from the author’s website.

Catalog no. K16087, April 2014, 208 pp.

ISBN: 978-1-4665-6520-3, $79.95 / £49.99 Also available as an eBook

Coming soon!

Biostatistics

SAS and R

A Computing Approach

Data Management, Statistical Analysis, and Graphics, Second Edition Ken Kleinman Harvard University, Boston, Massachusetts, USA

Nicholas J. Horton Amherst College, Massachusetts, USA

This widely praised book shows how equivalent statistical methods can be applied in either SAS or R, enabling users of each software package to learn how to apply the methods in the other. The book covers data management, simple statistical procedures, modeling, regression, and graphics. This second edition includes new entries on various statistical procedures. It also presents many new examples in a number of new chapters covering simulation, probability, statistics, mathematics/computing, and graphics.

Catalog no. K19040, June 2014, 487 pp.

ISBN: 978-1-4665-8449-5, $79.95 / £49.99 Also available as an eBook

Stewart J. Anderson University of Pittsburgh, Pennsylvania, USA

“The book presents important topics in biostatistics alongside examples provided in the programming languages SAS and R. … each chapter provides exercises encouraging the reader to deepen her/his understanding. I really like that the theory is presented in a clear manner without interruptions of example programs. Instead, the programs are always presented at the end of a section. … I can recommend this to all serious students who want to get a thorough start into this field.”

—Frank Emmert-Streib, CHANCE, August 2013

Catalog no. C8342, December 2011, 326 pp.

ISBN: 978-1-58488-834-5, $87.95 / £43.99 Also available as an eBook

For more information and complete contents, visit www.crcpress.com

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Epidemiology Bayesian Methods in Epidemiology

New!

Epidemiology Study Design and Data Analysis, Third Edition

Lyle D. Broemeling Broemeling and Associates, Medical Lake, Washington, USA

Mark Woodward University of Oxford, UK; University of Sydney, Australia; and Johns Hopkins University, Baltimore, Maryland, USA

Updated and expanded, this popular text focuses on the quantitative aspects of epidemiological research. It shows readers how statistical principles and techniques can help solve epidemiological problems.

Along with more exercises and examples using both Stata and SAS, this third edition includes a new chapter on risk scores and clinical decision rules, a new chapter on computer-intensive methods, and new sections on binomial regression models, competing risk, information criteria, propensity scoring, and splines. Supporting materials are available on the book’s CRC Press web page.

Written by a biostatistics expert with over 20 years of experience in the field, this book is the first to introduce epidemiology from a Bayesian perspective. It shows epidemiologists how Bayesian models and techniques are useful in studying the association between disease and exposure to risk factors. With many examples and end-of-chapter exercises, the book employs the software package WinBUGS to carry out the analyses and offers the code in the text and for download online.

• Represents the only book that introduces epidemiology from a Bayesian viewpoint • Presents a Bayesian approach for disease screening

• Covers the spectrum of statistical principles and analytical tools used in epidemiological research

• Explains the most useful models in epidemiology, including survival and regression models

• Explains how to design epidemiological studies and how to analyze the data from these studies

• Illustrates the techniques and models through real-world examples, including tumor registry data, a leukemia clinical trial, and health insurance data

• Uses data sets taken from real epidemiological investigations and publications to illustrate the concepts and methods • Assumes only a basic statistical background, emphasizing practical methods over complicated proofs • Includes extensive references for further reading as well as end-of-chapter exercises to reinforce understanding • Provides data sets, SAS and Stata programs, and more on the book’s CRC Press web page

Selected Contents: Fundamental Issues. Basic Analytical Procedures.

Assessing Risk Factors. Confounding and Interaction.

Cohort Studies. Case-Control Studies. Intervention Studies. Sample Size Determination. Modeling Quantitative Outcome Data. Modeling Binary Outcome Data. Modeling Follow-Up Data.

Meta-Analysis. Risk Scores and Clinical Decision Rules.

Computer-Intensive Methods. Appendices. Index.

Catalog no. K11828, December 2013, 898 pp.

ISBN: 978-1-4398-3970-6, $99.95 / £49.99 Also available as an eBook

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• Implements the analyses using WinBUGS, with the code available on the author’s website • Provides introductions to Bayesian inference for epidemiology and the use of WinBUGS in the appendices • Includes exercises and references at the end of each chapter

Selected Contents: Introduction to Bayesian Methods in Epidemiology.

A Bayesian Perspective of Association between Risk Exposure and Disease. Bayesian Methods of Adjustment of Data. Regression Methods for Adjustment. A Bayesian Approach to Life Tables.

A Bayesian Approach to Survival Analysis. Screening for Disease. Statistical Models for Epidemiology.

Appendices. Index.

Catalog no. K16074, August 2013, 464 pp.

ISBN: 978-1-4665-6497-8, $89.95 / £57.99 Also available as an eBook

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Epidemiology New!

Writing Dissertation and Grant Proposals Epidemiology, Preventive Medicine and Biostatistics Lisa Chasan-Taber University of Massachusetts, Amherst, USA

This book targets effective grant proposal writing in epidemiology, preventive medicine, and biostatistics.

It provides summary checklists and step-by-step guidelines for grant structure and style, critical do’s and don’ts that aid in writing solid grant proposals, and broader strategies for developing a research funding portfolio. Written by an established NIH reviewer, the book demonstrates proven tactics with extensive examples from successfully funded proposals. It serves as a virtual cookbook of the ingredients needed to construct a winning grant proposal.

• Focuses on effective grant proposal writing in epidemiology, preventive medicine, and biostatistics • Contains insight from an established NIH reviewer with an impressive track record of funding • Provides summary checklists and step-by-step guidelines for grant structure and style • Offers strategies for developing a research funding portfolio • Includes extensive examples from successfully funded grants

Selected Contents: Ten Top Tips for Successful Proposal Writing.

Starting a Dissertation Proposal. How to Develop and Write Hypotheses. Conducting the Literature Search.

Scientific Writing. Specific Aims. Background and Significance Section. Summarizing Preliminary Studies.

Study Design and Methods. Data Analysis Plan. Power and Sample Size. Review of Bias and Confounding.

How to Present Limitations and Alternatives.

Reproducibility and Validity Studies. Abstracts and Titles. Presenting Your Proposal Orally. Choosing the Right Funding Source. Submission of the Grant Proposal. Review Process. Resubmission of the Grant Proposal.

Catalog no. K14871, April 2014, 448 pp.

Soft Cover, ISBN: 978-1-4665-1206-1 $59.95 / £38.99 Also available as an eBook

Bayesian Disease Mapping Hierarchical Modeling in Spatial Epidemiology, Second Edition Andrew B. Lawson Medical University of South Carolina, Charleston, USA

This second edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications. A biostatistics professor and WHO advisor, the author illustrates the use of Bayesian hierarchical modeling in the geographical analysis of disease through a range of real-world datasets. This edition includes new chapters on regression and ecological analysis, putative hazard modeling, and disease map surveillance as well as new appendices featuring examples of INLA and CAR models. It also presents expanded material on case event modeling and spatiotemporal analysis.

Catalog no. K14543, March 2013, 396 pp.

ISBN: 978-1-4665-0481-3, $89.95 / £57.99 Also available as an eBook

Statistical Thinking in Epidemiology Yu-Kang Tu Mark S. Gilthorpe University of Leeds, UK

Addressing issues that have plagued researchers throughout the last decade, this book provides insight into the many existing problems in statistical modeling and offers several alternative strategies to approach these problems. The authors use specific examples in epidemiology to illustrate different model specifications that can imply different sets of causal relationships between variables. Each model is interpreted with regard to the context of implicit or explicit causal relationships. The authors also use vector geometry where applicable to provide an intuitive understanding of important statistical concepts.

Catalog no. K10018, July 2011, 231 pp.

ISBN: 978-1-4200-9991-1, $98.95 / £62.99 Also available as an eBook

For more information and complete contents, visit www.crcpress.com

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Medical Diagnostics

Statistical and Computational Methods in Brain Image Analysis Moo K. Chung University of Wisconsin-Madison, USA

Using MATLAB® and case study data sets, this is the first book to explicitly explain how to perform statistical analysis on brain imaging data. The book presents a coherent statistical and mathematical treatment of methods useful in neuroimaging applications. It illustrates the methods with real-world examples and case studies. The book includes many high-quality image visualization examples using MATLAB, with data and codes available on the author’s website.

Catalog no. K11644, July 2013, 416 pp.

ISBN: 978-1-4398-3635-4, $99.95 / £63.99 Also available as an eBook

Statistics of Medical Imaging

Statistical Evaluation of Diagnostic Performance Topics in ROC Analysis Kelly H. Zou, Aiyi Liu, Andriy I. Bandos, Lucila Ohno-Machado, and Howard E. Rockette “… a useful addition to the ROC literature, which will prove valuable for both those involved in medical diagnosis and those whose primary interest is ROC analysis itself.”

—David J. Hand, International Statistical Review (2013), 81, 2

“… a valuable starting point for those conducting basic research on ROC analysis and for applied researchers who are intrigued by the use of neat methodologies in applications.”

—ISCB News, June 2012

Catalog no. K10617, July 2011, 245 pp.

ISBN: 978-1-4398-1222-8, $98.95 / £62.99 Also available as an eBook

Time Series Modeling of Neuroscience Data

Tianhu Lei “Statistics of Medical Imaging is an in-depth and mathematical account of the statistics associated with medical imaging technologies, particularly x-ray CT and MR imaging. … the text is successful at developing a structured argument for the statistical properties with supporting background physics, mathematical proofs, and integrated statistical models for both x-ray CT and MRI.” —Camille Palmer, Health PhysicsThe Radiation Protection Journal, March 2013

Catalog no. C8842, December 2011, 438 pp.

ISBN: 978-1-4200-8842-7, $104.95 / £66.99 Also available as an eBook

Tohru Ozaki Institute of Statistical Mathematics, Tokyo, Japan

“This book is essential for every quantitative scientist who is interested in developing rigorous statistical models for analyzing brain signals. … it is truly unique in its treatment of the topic because it has an eye toward modeling brain signals … and thus builds on the specifics that are directly relevant to these particular data. … At the University of California, Irvine, researchers have used this book recently and found it to be very helpful.

Moreover, I intend to use this book as the primary text for a special topic course on neurostatistics in the Department of Statistics.”

—Hernando Ombao, Journal of Time Series Analysis, 2013

Catalog no. C4602, January 2012, 574 pp.

ISBN: 978-1-4200-9460-2, $104.95 / £66.99 Also available as an eBook

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Statistics for Life Sciences Coming soon!

New!

Statistical Methods in Biology

Foundational and Applied Statistics for Biologists Using R

Design and Analysis of Experiments and Regression Suzanne Jane Welham, Salvador Alejandro Gezan, Suzanne Jane Clark, and Andrew Mead Written in simple language with relevant examples, this introductory book presents best practices in experimental design and simple data analysis. Taking a practical and intuitive approach, it only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat® statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R. • Provides an introduction to both experimental design and linear regression • Takes an applied approach, with an emphasis on explaining the practical application of the methods through real examples and the use of software

Ken A. Aho Idaho State University, Pocatello, USA

Full of biological applications, exercises, and interactive graphical examples, this text presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment to enable readers to examine the code of complicated procedures step by step and thus better understand the process of obtaining analysis results. The graphical capabilities of R are used to provide interactive demonstrations of simple to complex statistical concepts. R code and other materials are available online.

• Covers a wide range of analytical topics, including bootstrapping, Bayesian MCMC procedures, regression, model selection, GLMs, GAMs, nonlinear models, ANOVA, mixed effects models, and permutation approaches • Emphasizes the understanding of statistical foundations • Provides R code for all analyses and uses R to generate the figures

• Focuses on examples and applications in the agricultural and biological sciences

• Includes many biological examples throughout and extensive exercises at the end of each chapter

• Includes implementation of the methods in both GenStat and R

• Reviews linear algebra applications and additional mathematical reference material in the appendix

• Offers problems and exercises in all the chapters

• Offers an introduction to R and R code for each chapter on the author’s website

Selected Contents: Introduction. A Review of Basic Statistics. Principles for Designing Experiments. Models for a Single Factor.

Checking Model Assumptions. Transformations of the Response. Models with Simple Blocking Structure.

Extracting Information about Treatments. Models with Complex Blocking Structure. Replication and Power.

Dealing with Non-Orthogonality. Models for a Single Variate: Simple Linear Regression. Checking Model Fit. Models for Several Variates: Multiple Linear Regression.

Models for Variates and Factors. Incorporating Structure: Mixed Models. Models for Curved Relationships. Models for Non-Normal Responses: Generalized Linear Models. Practical Design and Data Analysis for Real Studies. References. Appendices.

Selected Contents: FOUNDATIONS: Philosophical and Historical Foundations. Introduction to Probability. Probability Density Functions. Parameters and Statistics. Interval Estimation: Sampling Distributions, Resampling Distributions, and Simulation Distributions. Hypothesis Testing. Sampling Design and Experimental Design.

APPLICATIONS: Correlation. Regression. ANOVA. Tabular Analyses. Appendix. References. Index.

Catalog no. K13403, December 2013, 618 pp.

ISBN: 978-1-4398-7338-0, $69.95 / £44.99 Also available as an eBook

Catalog no. K10432, July 2014, c. 552 pp.

ISBN: 978-1-4398-0878-8, $79.95 / £49.99 Also available as an eBook

For more information and complete contents, visit www.crcpress.com

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Statistical Genetics New!

Coming soon!

Bayesian Phylogenetics Methods, Algorithms, and Applications Edited by

Ming-Hui Chen, Lynn Kuo, and Paul O. Lewis University of Connecticut, Storrs, USA

Suitable for graduate-level researchers in statistics and biology, this book offers a snapshot of current trends in Bayesian phylogenetic research. It emphasizes model selection, reflecting recent interest in accurately estimating marginal likelihoods. The book discusses new approaches to improve mixing in Bayesian phylogenetic analyses in which the tree topology varies. It also covers divergence time estimation, biologically realistic models, and the burgeoning interface between phylogenetics and population genetics.

• Explores current research in Bayesian phylogenetics of interest to both the statistics and biology communities • Covers model selection, efficient computational algorithms, priors, recombination, phylodynamics, evolutionary dependence, and divergence time estimation • Encourages interdisciplinary research to solve theoretical and computational challenges

Selected Contents: Bayesian phylogenetics: methods, computational algorithms, and applications. Priors in Bayesian phylogenetics. IDR for marginal likelihood in Bayesian phylogenetics. Bayesian model selection in phylogenetics and genealogy-based population genetics. Variable tree topology stepping-stone marginal likelihood estimation. Consistency of marginal likelihood estimation when topology varies.

Bayesian phylogeny analysis. Sequential Monte Carlo (SMC) for Bayesian phylogenetics. Population model comparison using multi-locus datasets. Bayesian methods in the presence of recombination. Bayesian nonparametric phylodynamics. Sampling and summary statistics of endpoint-conditioned paths in DNA sequence evolution. Bayesian inference of species divergence times. Index.

Catalog no. K14380, June 2014, c. 398 pp.

ISBN: 978-1-4665-0079-2, $99.95 / £63.99 Also available as an eBook

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Statistical Methods for QTL Mapping Zehua Chen National University of Singapore

While numerous advanced statistical approaches have recently been developed for quantitative trait loci (QTL) mapping, the methods are scattered throughout the literature. This book brings together many recent statistical techniques that address the data complexity of QTL mapping. It emphasizes the modern statistical methodology for QTL mapping as well as the statistical issues that arise during this process. The book gives the necessary biological background for statisticians without training in genetics and, likewise, covers statistical thinking and principles for geneticists.

Catalog no. K13106, November 2013, 308 pp.

ISBN: 978-1-4398-6830-0, $89.95 / £57.99 Also available as an eBook

Stochastic Modelling for Systems Biology Second Edition Darren J. Wilkinson Newcastle University, UK

“Each chapter is completed by some training exercises. … the author also proposes further readings in a dedicated section for each chapter, which is in my opinion a really good idea … the book is supplemented by a quite complete website. … the book has been enhanced by an introduction to approximate Bayesian computation, the codes have been updated to SBML Level 3, and the chapters on Markov chains and stochastic differential equations have been reinforced. … a really comprehensible and easy-to-read course.”

—Sophie Donnet, CHANCE, 25.4

Catalog no. K11715, November 2011, 363 pp.

ISBN: 978-1-4398-3772-6, $98.95 / £62.99 Also available as an eBook

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