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Cover image courtesy of the American Statistical Association

Contents Introductory Statistics and General References ....3 Statistical Theory and Methods ............................4 Biostatistics and Epidemiology............................13 Computational Statistics ....................................20 Statistical Learning and Data Mining..................23 Page 4

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Statistics for Business, Finance, and Economics....24 Statistics for the Social and Behavioral Sciences....27 Environmental Statistics ......................................28 Statistics for Engineering and Physical Science....30

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Introductory Statistics and General References The BUGS Book A Practical Introduction to Bayesian Analysis David Lunn, Chris Jackson, Nicky Best, Andrew Thomas, and David Spiegelhalter “The most anticipated applied Bayesian text of the last 20 years, The BUGS Book is like a wonderful album by an established rock supergroup … the authors have created a masterpiece well worth the wait. The book offers the perfect mix of basic probability calculus, Bayes and MCMC basics, an incredibly broad array of useful statistical models, and a BUGS tutorial and user manual complete with all the ‘tricks’ one would expect from the team that invented the language. … accessible yet comprehensive instruction in its proper use. A must-own for any working applied statistical modeler.”

—Bradley P. Carlin, University of Minnesota

“If a book has ever been so much desired in the world of statistics, it is for sure this one. … it reflects very well the aims and spirit of the BUGS project and is meant to be a manual ‘for anyone who would like to apply Bayesian methods to real-world problems.’ … a mandatory [book] for all statisticians willing to learn and analyze data with Bayesian statistics at any level. …”

—Jean-Louis Fouley, CHANCE, 2013

• Covers all the functionalities of BUGS, including prediction, missing data, model criticism, and prior sensitivity

Paradoxes in Scientific Inference Mark Chang AMAG Pharmaceuticals, Inc, Lexington, Massachusetts, USA

The paradoxology of scientific inference refers to the study of the nature of scientific inference and evidence through controversies or, more precisely, paradoxes. This book analyzes paradoxes from many different perspectives, such as statistics, mathematics, philosophy, science, and artificial intelligence. It compares various quantitative methods of evidence measures, including frequentist hypothesis testing, likelihood, and Bayesian methods. Other topics covered include probability, plausible reasoning, multiplicity, and inferences.

The text elaborates on recent findings to reach new and exciting conclusions. It challenges readers’ knowledge, intuition, and conventional wisdom, compelling them to adjust their way of thinking.

Ultimately, readers will learn effective scientific inference through studying the paradoxes.

• Presents large collections of paradoxes in the sciences and statistics • Provides broad and interesting applications of paradoxes • Offers a new, effective way of learning scientific inference • Analyzes controversies in statistical measures of scientific evidence

• Features a large number of worked examples and applications from a wide range of disciplines

• Discusses principles and the conceptual unification of statistical paradigms

• Includes detailed exercises and solutions on a supporting website

• Develops new architectures for creating artificial intelligent agents

Selected Contents:

• Includes a quick study guide and exercises in each chapter

Introduction: Probability and Parameters. Monte Carlo Simulations using BUGS. Introduction to Bayesian Inference. Introduction to Markov Chain Monte Carlo Methods. Prior Distributions. Regression Models. Categorical Data. Model Checking and Comparison. Issues in Modeling. Hierarchical Models. Specialized Models. Different Implementations of BUGS. Appendices. Bibliography.

Index.

Catalog no. C8490, October 2012, 399 pp.

Soft Cover ISBN: 978-1-58488-849-9, $49.95 / £24.99

Selected Contents: The Joy of Paradoxes: A Random Walk. Mathematical and Plausible Reasoning. Statistical Measures of Scientific Evidence. Scientific Principles and Inferences. Artificial Intelligence. Appendix.

Bibliography. Index.

Catalog no. K14744, October 2012, 291 pp.

Soft Cover ISBN: 978-1-4665-0986-3, $39.95 / £25.99 Also available as an eBook

Also available as an eBook

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

3

Introductory Statistics and General References / Statistical Theory and Methods

The R Student Companion

The A-Z of Error-Free Research

Brian Dennis

Phillip I. Good

University of Idaho, Moscow, USA

Consultant, Huntington Beach, California, USA

“An R book for high schoolers! This is an excellent idea, and the quality of the product is equally excellent. It may be suitable for non-calculus-based introductory courses at the college level as well. … Dennis does a good job dispelling the ‘steep learning curve’ myth concerning R … It is high time that introductory statistics be taught in an engaging manner … with meaningful data sets, attractive graphics, and so on. Dennis’ book is a fine contribution toward that goal.”

This practical book begins with an overview of when—and when not—to use statistics. It guides readers through the planning and data collection phases and presents various data analysis techniques.

The author then covers techniques for developing models that provide a basis for future research. He also discusses reporting techniques to ensure research efforts get the proper credit. The book concludes with case-control and cohort studies. R code is included to implement the methods.

—Norman Matloff, Journal of Statistical Software, February 2013

Catalog no. K13498, September 2012, 360 pp.

Soft Cover ISBN: 978-1-4398-7540-7, $39.95 / £25.99

R for Statistics Pierre-Andre Cornillon, Arnaud Guyader, Francois Husson, Nicolas Jegou, Julie Josse, Maela Kloareg, Eric Matzner-Lober, and Laurent Rouvière “Section 4.2 on the apply family of functions and related functions for matrices, arrays, and data frames is by far the most friendly and helpful introduction to the subject that I have seen. … All datasets, along with the R code in the book, are available on the website for the text. … If you are not a trained programmer but you aspire to write code that is efficient and perhaps, from time to time, clever, then this book is a fine place for you to start learning R.” —Homer S. White, MAA Reviews, January 2013

Catalog no. K13834, March 2012, 320 pp.

Soft Cover ISBN: 978-1-4398-8145-3, $59.95 / £34.99 Also available as an eBook

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Catalog no. K14287, August 2012, 269 pp.

Soft Cover ISBN: 978-1-4398-9737-9, $49.95 / £31.99

Coming soon!

Exercises and Solutions in Statistical Theory Lawrence L. Kupper, Brian H. Neelon, and Sean M. O’Brien Designed for teaching a statistical theory course in statistics, biostatistics, mathematics, engineering, physics, computer science, psychometrics, and other disciplines, this text contains exercises and selected solutions in probability theory, univariate distribution theory, and multivariate distribution theory as well as exercises and selected solutions in estimation theory and hypothesis testing theory. The exercises vary in difficulty from basic to intermediate to advanced.

Solutions for about half the exercises are included, with a separate solutions manual available upon qualifying course adoption.

Catalog no. K16626, May 2013, c. 390 pp.

Soft Cover ISBN: 978-1-4665-7289-8, $59.95 / £38.99 Also available as an eBook

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Statistical Theory and Methods Coming soon!

Coming soon!

Linear Algebra and Matrix Analysis for Statistics

Statistical Theory A Concise Introduction

Sudipto Banerjee

Felix Abramovich

University of Minnesota, Minneapolis, USA

Tel Aviv University, Israel

Ya'acov Ritov

Anindya Roy

The Hebrew University of Jerusalem, Israel

University of Maryland Baltimore County, USA

“This beautifully written text is unlike any other in statistical science. It starts at the level of a first undergraduate course in linear algebra, and takes the student all the way up to the graduate level, including Hilbert spaces. It is extremely well crafted and proceeds up through that theory at a very good pace. The statistics chapters are added at just the right places to motivate the reader and illustrate the theory. The book is compactly written and mathematically rigorous, yet the style is lively as well as engaging. This elegant, sophisticated work will serve upper level and graduate statistics education well.

All and all a book I wish I could have written.”

—Jim Zidek, University of British Columbia

• Provides an overview of linear algebra and matrix analysis for statistical applications • Takes a vector-space approach, enabling elegant proofs and smooth transition to more complex topics • Presents recent developments in fields as diverse as spatial statistics, machine learning, and social network analysis

This text presents a clear introduction to statistical theory for advanced undergraduate students taking a standard course in statistics. It details the main elements and basic concepts of statistical theory, including parameter estimation, confidence intervals, hypothesis testing, Bayesian interference, and decision theory.

The book takes an examples-based approach with clear exposition of key topics and just the right amount of mathematical formality. It also includes numerous exercises to enhance the students’ understanding of the topics discussed.

• Presents a clear and concise introduction to the key topics of statistical theory • Offers the right balance of exposition and mathematical formality • Introduces topics with illustrative examples, avoiding a dry approach to the subject • Includes numerous exercises to facilitate teaching or self-study

Selected Contents:

• Includes exercises to enable further understanding of the topics discussed

Introduction. Parameter Estimation. Confidence Intervals and Confidence Regions. Large-Sample Theory. Hypotheses Testing. Bayesian Inference.

Elementary Decision Theory.

Selected Contents:

Catalog no. K12383, May 2013, c. 239 pp.

ISBN: 978-1-4398-5184-5, $69.95 / £44.99

• Requires no prior knowledge of linear algebra

Basic Operations. Systems of Linear Equations. More on Linear Equations. Euclidean Spaces. The Rank of a Matrix. Complementary Subspaces. Orthogonality, Orthogonal Subspaces, and Projections. More on Orthogonality. Revisiting Linear Equations.

Determinants. Eigenvalues and Eigenvectors.

Quadratic Forms. Matrix and Vector Norms. Hilbert Spaces. References.

Also available as an eBook

Catalog no. K10023, September 2013, c. 416 pp.

ISBN: 978-1-4200-9538-8, $79.95 / £49.99 Also available as an eBook

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5

Statistical Theory and Methods New!

Understanding Advanced Statistical Methods Peter Westfall Texas Tech University, Lubbock, USA

Kevin S.S. Henning Sam Houston State University, Huntsville, Texas, USA

Probability and Stochastic Modeling Vladimir I. Rotar San Diego State University, California, USA

Designed for students in all disciplines, this text introduces mathematical statistics in intuitive, self-contained, and accessible ways. Simulations and computing are used throughout to introduce and illustrate topics. Many exercises and examples span various scientific disciplines. The book discusses Bayesian statistics before frequentist statistics, thoroughly covers populations versus processes, integrates design and measurement with analysis, and emphasizes the understanding and use of statistical models as recipes for producing data.

“This is a superbly written text on probability and stochastic processes for … upper division students in science and engineering, including statistics and mathematics, as well as students in fields such as economics and finance. … a wonderful book for self study for many others. Important and well-chosen examples illustrate the theory throughout, and a large body of exercises supplements the text. … A special feature of this book is a marvelous exposition of many interesting aspects of financial mathematics that are generally considered rather intricate and inaccessible at this level. …”

• Provides a unique and accessible scientifically based introduction to topics of mathematical statistics

Catalog no. K13311, August 2012, 508 pp.

ISBN: 978-1-4398-7206-2, $79.95 / £49.99

• Emphasizes simulation and computing with many data examples • Presents the necessary concepts in calculus and probability in a very intuitive way • Includes numerous exercises, enabling use as a course text or for self-study

Selected Contents: Introduction: Probability, Statistics and Science.

Random Variables and Their Probability Distributions.

Probability Calculation and Simulation. Identifying Distributions. Conditional Distributions and Independence. Marginal Distributions, Joint Distributions, Independence, and Bayes’ Theorem.

Sampling from Populations and Processes. Expected Value and the Law of Large Numbers. Functions of Random Variables: Their Distributions and Expected Values. Distributions of Totals. Estimation: Unbiasedness, Consistency, and Efficiency. The Likelihood Function and Maximum Likelihood Estimates. Bayesian Statistics. Frequentist Statistical Methods. Are Your Results Explainable by Chance Alone? Chi-Squared, Student’s t, and F-Distributions, with Applications. Likelihood Ratio Tests. Sample Size and Power. Robustness and Nonparametric Methods.

Catalog no. K14873, April 2013, c. 567 pp.

ISBN: 978-1-4665-1210-8, $79.95 / £44.99

—Rabi Bhattacharya, University of Arizona

Also available as an eBook

Coming soon!

Statistical Methods for Handling Incomplete Data Jae Kwang Kim and Jun Shao With advances in computing power, there have been substantial developments in computational methods for handling missing data. This text presents an introduction to the theory, applications, and computational aspects of missing data analysis. It covers the three main methodological approaches: likelihood-based, nonparametric, and quasi-randomization. The text includes many real examples and integrates computer code where appropriate. It also provides exercises at the end of each chapter.

Catalog no. K12249, August 2013, c. 224 pp.

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

Also available as an eBook

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Statistical Theory and Methods

Flexible Imputation of Missing Data Stef van Buuren

Principles of Uncertainty Joseph B. Kadane Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

TNO Quality of Life, Leiden, The Netherlands

2011 Degroot Prize Winner

“It’s excellent and I highly recommend it. … van Buuren’s book is great even if you don’t end up using the algorithm described in the book … he supplies lots of intuition, examples, and graphs.”

“In this remarkable book, Kadane begins at the most rudimentary level, develops all the needed mathematics on the fly, and still manages to flesh out at least the core of the whole story, slowly, thoughtfully, and rigorously, right up to graduate level. Major theorems all proved in detail appear here, but not for their own sake; the author always carefully selects them … . Highly recommended.”

—Andrew Gelman, Columbia University

“… a beautiful book that is so full of guidance for statisticians … exceptionally up to date and has more useful wisdom about dealing with common missing data problems than any other source I’ve seen.”

—Frank Harrell, Vanderbilt University

Catalog no. K13103, March 2012, 342 pp.

ISBN: 978-1-4398-6824-9, $89.95 / £57.99

—D.V. Feldman, CHOICE, February 2012

Catalog no. K12848, May 2011, 503 pp.

ISBN: 978-1-4398-6161-5, $89.95 / £59.99 Also available as an eBook

Also available as an eBook

Maximum Likelihood Estimation for Sample Surveys Raymond L. Chambers, David G. Steel, Suojin Wang, and Alan Welsh This book presents an overview of likelihood methods for the analysis of survey data obtained using methods that may result in the sample differing from the population. It provides all necessary background material on likelihood inference and covers a range of data types, including multilevel data. Illustrated by numerous worked examples using tractable models, it also addresses advanced topics such as combining data, non-response, and informative sampling.

Catalog no. C6323, May 2012, 391 pp.

ISBN: 978-1-58488-632-7, $79.95 / £49.99 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

This self-contained text explains how to perform the statistical analysis of discrete data. It covers classic concepts and popular topics, such as contingency tables, logistic models, and Poisson regression models. It also presents modern areas that include models for zeromodified count outcomes, parametric and semiparametric longitudinal data analysis, reliability analysis, and methods for dealing with missing values. 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, $89.95 / £57.99 Also available as an eBook

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7

Statistical Theory and Methods New!

Generalized Linear Models and Extensions

Generalized Estimating Equations

Third Edition James W. Hardin

Second Edition James W. Hardin University of South Carolina, Columbia, USA

Joseph M. Hilbe California Institute of Technology, Pasadena, and Arizona State University, Tempe, USA

Praise for the First Edition: “Generalized Estimating Equations is the first and only book to date dedicated exclusively to GEEs. …

The authors do a good job of not only presenting the general theory of GEE models, but also giving explicit examples of various correlation structures, link functions, and a comparison between population-averaged and subject-specific models. … a valuable reference for researchers, teachers, and students who study and practice GLIM methodology.”

—Journal of the American Statistics Association, March 2004

This second edition of a bestseller incorporates comments and suggestions from a variety of sources, including the Statistics.com course on longitudinal and panel models taught by the authors. Along with doubling the number of end-of-chapter exercises, this edition offers more thorough coverage of hypothesis testing and diagnostics, expands discussion of various models associated with GEE, and provides a new presentation of model selection procedures. Numerous examples are employed throughout the text, along with the software code used to create, run, and evaluate the models being examined.

• Provides an overview of the theory and applications of GEEs

University of South Carolina, Columbia, USA

Joseph M. Hilbe California Institute of Technology, Pasadena, and Arizona State University, Tempe, USA

This book presents a thorough examination of GLM estimation methods as well as the derivation of all major GLM families. Examined families include Gaussian, gamma, inverse Gaussian, binomial, Poisson, geometric, and negative binomial. The text also contains various models that have been developed on the basis of GLM theory. Using Stata, the book offers numerous examples to assist readers in applying the models to their own data situations.

Catalog no. N10590, June 2012, 479 pp.

Soft Cover ISBN: 978-1-59718-105-1, $79.95 / £49.99

Confidence Intervals for Proportions and Related Measures of Effect Size

• Adopts a practical approach with many examples

Robert G. Newcombe

• Contains new methods and examples

This book illustrates the use of effect size measures and corresponding confidence intervals as more informative alternatives to the most basic and widely used significance tests. It provides readers with a deep understanding of what happens when these statistical methods are applied in situations far removed from the familiar Gaussian case. Requiring little computational skills, the book offers user-friendly Excel spreadsheets for download at www.crcpress.com, enabling readers to easily apply the methods to their own empirical data.

• Includes theoretical details in the appendices • Offers Stata, SAS, and R code for the examples, with the code and data sets available online

Selected Contents: Introduction. Model Construction and Estimating Equations. Generalized Estimating Equations.

Residuals, Diagnostics, and Testing. Programs and Datasets. References. Author Index. Subject Index.

Catalog no. K13819, December 2012, 277 pp.

ISBN: 978-1-4398-8113-2, $89.95 / £57.99 Also available as an eBook

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Cardiff University, Wales

Catalog no. K10649, August 2012, 468 pp.

ISBN: 978-1-4398-1278-5, $89.95 / £57.99 Also available as an eBook

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Statistical Theory and Methods Generalized Linear Mixed Models Modern Concepts, Methods and Applications Walter W. Stroup University of Nebraska, Lincoln, USA

This text presents an introduction to linear modeling using the GLMM as an overarching conceptual framework. For readers new to linear models, the book helps them see the big picture. It shows how linear models fit with the rest of the core statistics curriculum and points out the major issues that statistical modelers must consider.

Methodology in Robust and Nonparametric Statistics Jana Jureˇcková, Pranab Kumar Sen, and Jan Picek

• Provides a true introduction to linear modeling that assumes data need not be normally distributed and assumes random model effects to be the rule not an advanced exception

Closely related to nonparametric methods, robust statistical methods are not unduly affected by data outliers or other small departures from model assumptions. This book presents a comprehensive overview of methodology for robust and nonparametric statistics. It covers both methods in parallel to demonstrate their relative strengths and weaknesses. Using examples to illustrate the methods, the text emphasizes applications in the fields of biomedical science, bioinformatics, finance, and engineering. Numerous exercises are also included in the text.

• Emphasizes the connection between study design and all aspects of the model

Catalog no. K11885, July 2012, 410 pp.

ISBN: 978-1-4398-4068-9, $99.95 / £63.99

• Includes a chapter on GLMM-based power and sample size assessment—a critical tool for cost-effective design of research studies

Also available as an eBook

• Presents numerous examples using the SAS® GLIMMIX procedure • Gives in-depth treatments of issues unique to generalized and mixed linear modeling, including conditional versus marginal modeling, broad versus narrow inference space, and data versus model-scale inference and reporting • Offers the data for all exercises as well as SAS files for all examples at www.crcpress.com

Selected Contents: PART I The Big Picture: Modeling Basics. Design Matters. Setting the Stage. PART II Estimation and Inference Essentials: Estimation. Inference, Part I: Model Effects. Inference, Part II: Covariance Components. PART III Working with GLMMs: Treatment and Explanatory Variable Structure.

Multilevel Models. Best Linear Unbiased Prediction.

Rates and Proportions. Counts. Time-to-Event Data.

Multinomial Data. Correlated Errors, Part I: Repeated Measures. Correlated Errors, Part II: Spatial Variability.

Power, Sample Size, and Planning. Appendices.

References. Index.

Catalog no. K10775, September 2012, 555 pp.

ISBN: 978-1-4398-1512-0, $89.95 / £57.99 Also available as an eBook

Extreme Value Methods with Applications to Finance Serguei Y. Novak Middlesex University, London, UK

“… there are many new techniques and results which do not exist in other books on extreme value theory. … those who want to study in detail the nonparametric methods for heavy-tailed distributions will find this book a very valuable contribution. … I would strongly recommend this book to PhD students working on extreme value theory [and] to mathematicians, probabilists, and statisticians who want to know about extreme value theory and nonparametric methods of inference for extremes.”

—K.F. Turkman, Journal of Times Series Analysis, March 2012

Catalog no. K11611, December 2011, 399 pp.

ISBN: 978-1-4398-3574-6, $104.95 / £66.99 Also available as an eBook

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Statistical Theory and Methods Coming soon!

Coming soon!

Analysis of Variance for Functional Data Jin-Ting Zhang National University of Singapore

This book presents the updated hypothesis testing methods developed in the last decade for FDA. The subjects covered include reconstructing functional observations, Gaussian processes, analysis of variance for functional data, functional linear models, ill-conditioned functional linear models, diagnostics of functional observations, variable selection for functional linear models, Behrens-Fisher problems for functional data, test of equal covariance functions, and surface data analysis.

Catalog no. K12912, June 2013, c. 333 pp.

ISBN: 978-1-4398-6273-5, $99.95 / £63.99 Also available as an eBook

Mean Field Simulation for Monte Carlo Integration Pierre Del Moral University of Bordeaux, Talence, France

This book deals with both the theoretical foundations and applications of sequential Monte Carlo methods and genetic-type particle techniques. These stochastic interacting particle algorithms belong to the class of advanced Monte Carlo methods. The book shows how these powerful computational methods are currently used in computational physics, physical chemistry, and computational biology for simulating complex systems in high dimensions.

• Provides a pedagogical introduction to the stochastic modeling and theoretical analysis of interacting particle algorithms • Gives a brief, self-contained account of modern mathematical theory useful for analyzing the asymptotic behavior of Feynman-Kac and particle models • Focuses on finite/countable state-space models • Presents theoretical probabilistic tools to analyze the performance of sequential Monte Carlo methods and genetic particle algorithms

Time Series Modeling of Neuroscience Data

Selected Contents:

Tohru Ozaki Institute of Statistical Mathematics, Tokyo, Japan

Due to recent advances in methodology that offer significant improvements over conventional methods, there is increasing interest in the use of time series models for the study of neuroscience data such as EEG, MEG, fMRI, and NIRS. Accessible to applied statisticians as well as quantitatively trained neuroscientists, this book includes many real examples that illustrate the methods and provides useful instructions for computational problems, enabling readers to develop their own computational toolbox to apply the methods to real data.

Sequential Monte Carlo and Genetic Particle Models: Introduction. Positive Matrices and Particle Recipes. Some Advanced Particle Recipes.

Application Domains: Particle Absorption Models.

Markov Chain Analysis. Biology and Chemistry Models. Signal Processing and Bayesian Inference.

Interacting Filters. Optimal Control Problems.

Markov Chain Monte Carlo Models. Interacting Stochastic Algorithms. Financial Mathematics.

Stochastic Optimization Algorithms. Rare Events Stochastic Models. Theoretical Aspects: A Brief Treatise on Feynman-Kac Modeling. Semigroup Analysis. Interacting Particle Algorithms. Advanced Stochastic Analysis Recipes. Unnormalized and Path Space Particle Measure. Bibliography. Index.

Catalog no. K14505, May 2013, c. 600 pp.

ISBN: 978-1-4665-0405-9, $99.95 / £63.99 Also available as an eBook

Catalog no. C4602, January 2012, 574 pp.

ISBN: 978-1-4200-9460-2, $99.95 / £63.99 Also available as an eBook

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Statistical Theory and Methods New!

New!

Statistical Methods with Applications to Demography and Life Insurance

Analysis of Mixed Data Edited by

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

Estáte V. Khmaladze

Keumhee Carrière Chough

Victoria University of Wellington, New Zealand

University of Alberta, Edmonton, Canada

Suitable for statisticians, mathematicians, actuaries, and students interested in the problems of insurance and analysis of lifetimes, this book presents contemporary statistical techniques for analyzing life distributions and life insurance problems. It not only contains traditional material but also incorporates new problems and techniques not discussed in existing actuarial literature.

This is the first volume to date that provides a unified and timely summary of the major advances in the field of mixed models. The book traces important developments, collates basic results, presents terminology and methodologies, and gives an overview of statistical research applications.

• Provides an easy transition from pure mathematics to demography and life insurance applications • Illustrates precise mathematical statements through real-world statistical problems • Includes new problems and techniques not covered in existing actuarial literature

• Illustrates modern methods and case studies using interesting applications from economics, medicine and health, marketing, and genetics • Includes contributions from major researchers on mixed data analysis • Explores future research directions

Selected Contents:

Duration of Life as a Random Variable. Models of Distribution Functions F(x) and Force of Mortality µ(x). The Empirical Distribution Function of Duration of Life. Deviation of Fn(x) from F(x) as a Random Process. Limit of Empirical Process: Brownian Bridge.

Distribution of x2 Goodness-of-Fit Statistic. Statistical Consequences of What We Have Learned So Far. Testing Parametric Hypotheses. Unexpected Example—Exponentiality of Durations of Rule of Roman Emperors. Estimation of the Rate of Mortality.

Censored Observations. Related Point Processes.

Kaplan-Meier Estimator (Product-Limit Estimator) for F. Statistical Inference about F Based on the KaplanMeier Estimator. Life Insurance and Net Premiums.

More on Net Premiums. Endowments and Annuities.

Annuities Certain. Some Problems of General Theory.

Right-Tail Behavior of Fn. Non-Parametric Confidence Bounds for Expected Remaining Life. Population Dynamics. Bibliography. Index.

Analysis of Mixed Data: An Overview. Combining Univariate and Multivariate Random Forests for Enhancing Predictions of Mixed Outcomes. Joint Tests for Mixed Traits in Genetic Association Studies.

Bias in Factor Score Regression and a Simple Solution. Joint Modeling of Mixed Count and Continuous Longitudinal Data. Factorization and Latent Variable Models for Joint Analysis of Binary and Continuous Outcomes. Regression Models for Analyzing Clustered Binary and Continuous Outcomes under the Assumption of Exchangeability.

Random Effects Models for Joint Analysis of Repeatedly Measured Discrete and Continuous Outcomes. Hierarchical Modeling of Endpoints of Different Types with Generalized Linear Mixed Models. Joint Analysis of Mixed Discrete and Continuous Outcomes via Copula Models. Analysis of Mixed Outcomes in Econometrics: Applications in Health Economics. Sparse Bayesian Modeling of Mixed Econometric Data Using Data Augmentation.

Bayesian Methods for the Analysis of Mixed Categorical and Continuous (Incomplete) Data.

Catalog no. K14582, March 2013, 242 pp.

ISBN: 978-1-4665-0573-5, $79.95 / £49.99

Catalog no. K13979, January 2013, 262 pp.

ISBN: 978-1-4398-8471-3, $89.95 / £57.99

Also available as an eBook

Also available as an eBook

Selected Contents:

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

11

Statistical Theory and Methods Coming soon!

Stationary Stochastic Processes for Scientists and Engineers

Stationary Stochastic Processes Theory and Applications

Georg Lindgren, Holger Lennart Rootzen, and Maria Sandsten

Georg Lindgren Lund University, Sweden

“In many respects, Lindgren’s Stationary Stochastic Processes: Theory and Applications is an updated and expanded version that has captured much of the same spirit (and topics!) as the Cramer and Leadbetter classic. While there have been a number of new and good books published recently on spatial statistics, none cover some of the key important topics, such as sample path properties and level crossings, in a comprehensive and understandable fashion like Lindgren’s book. This book is required reading for all of my PhD students working in spatial statistics and related areas.”

—Richard A. Davis, Columbia University

“This book offers quite a unique approach and selection of topics within the modern field of stochastic processes. … those coming from the theoretical side who want to know more about the applications will benefit from this book. A common theme for the book is the bridge-building between different audiences. … Without being mathematically overdemanding, the book builds up the relevant theory in a very intuitive yet rigorous way that helps the reader to a deeper understanding of definitions and results that could otherwise be mystifying. This intuition-driven approach also provides a common thread throughout the book.”

—Claudia Klüppelberg and Morten Grud Rasmussen, Technische Universität München

Selected Contents: Some Probability and Process Background. Sample Function Properties. Spectral Representations. Linear Filters: General Properties. Linear Filters: Special Topics. Classical Ergodic Theory and Mixing. Vector Processes and Random Fields. Level Crossings and Excursions.

“This book is a lucid and well-paced introduction to stationary stochastic processes, superbly motivated and illustrated through a wealth of convincing applications in science and engineering. It offers a clear guide to the formulation and mathematical properties of these processes and to some non-stationary processes too, without going too deeply into the mathematical foundations; the emphasis throughout is on practical application rather than mathematical development for its own sake. The reader will find tools for analysis and calculation and also—importantly—material to deepen understanding and generate enthusiasm and confidence.

An outstanding text.”

—Clive Anderson, University of Sheffield

Based on a course taught to undergraduate students in engineering for over 30 years, this text presents all the material for a first course in stationary stochastic processes (SSP). Following naturally from a mathematical statistics course, it covers model building via SSP with a focus on engineering applications. The book includes many exercises and computer-based practicals using MATLAB®.

• Focuses on engineering topics and applications • Draws on classroom-tested material • Presents covariance and Fourier methods, including linear filters in discrete and continuous time • Describes statistical estimation techniques, mainly for frequency analysis • Incorporates exercises and MATLAB-based lab sessions Catalog no. K20279, August 2013, c. 300 pp.

ISBN: 978-1-4665-8618-5, $79.95 / £49.99

Catalog no. K15489, October 2012, 375 pp.

ISBN: 978-1-4665-5779-6, $89.95 / £57.99 Also available as an eBook

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Statistical Theory and Methods / Biostatistics and Epidemiology Statistical Methods for Stochastic Differential Equations Edited by

Mathieu Kessler, Alexander Lindner, and Michael Sorensen This book presents current research trends and recent developments in statistical methods for stochastic differential equations. Accessible both to new students and seasoned researchers, each self-contained chapter starts with introductions to the topics and builds gradually toward discussing recent research. Written by leading researchers in the field, the book includes applications to finance and econometrics and provides relevant software where applicable.

Catalog no. K12236, May 2012, 507 pp.

ISBN: 978-1-4398-4940-8, $99.95 / £63.99 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

“This second edition remains a useful reference source for anyone interested in advancing innovative trial designs and wishing to incorporate adaptations, modifications, and changes to the drug development process. Five new chapters have been added and are all worth reading … . For anyone working in and studying clinical research, the book is worth purchasing and will make a valuable addition to any library. … this revision continues to provide a balanced summary of statistical methods, together with the authors’ perspective on current regulatory practice.”

—International Statistical Review, 80, 2012

Catalog no. K11837, December 2011, 374 pp.

ISBN: 978-1-4398-3987-4, $89.95 / £59.99 Also available as an eBook

Design and Analysis of Bridging Studies Edited by

Jen-pei Liu, Shein-Chung Chow, and Chin-Fu Hsiao Taking into account the International Conference Harmonisation E5 framework for bridging studies, this book covers the regulatory requirements, scientific and practical issues, and statistical methodology for designing and evaluating bridging studies and multiregional clinical trials. For bridging studies, the authors explore ethnic sensitivity, the necessity of bridging studies, types of bridging studies, and the assessment of similarity between regions based on bridging evidence. For multiregional clinical trials, the text considers regional differences, assesses the consistency of treatment effect across regions, and discusses sample size determination for each region.

Catalog no. K12075, July 2012, 287 pp.

ISBN: 978-1-4398-4634-6, $99.95 / £63.99 Also available as an eBook

Design and Analysis of NonInferiority Trials Mark D. Rothmann, Brian L. Wiens, and Ivan S.F. Chan “… an important resource for anyone involved in designing non-inferiority trials. The authors weave in many examples, primarily in oncology, as well as a large set of references from the now substantial statistical literature on non-inferiority designs. … a must-have resource … . A portion of a special topics course in a biostatistics department could be built around this book, and this exposure would be especially valuable for students considering a career in or around the pharmaceutical industry.”

—Erica Brittain, Australian & New Zealand Journal of Statistics, May 2012

Catalog no. C8040, July 2011, 454 pp.

ISBN: 978-1-58488-804-8, $93.95 / £59.99 Also available as an eBook

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

13

Biostatistics and Epidemiology Coming soon!

Biosimilars

Coming soon!

Design and Analysis of Follow-on Biologics Shein-Chung Chow

Randomized Phase II Cancer Clinical Trials

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

Sin-Ho Jung Duke University, Durham, North Carolina, USA

This is the first book entirely devoted to the design and analysis of biosimilarity assessment and drug interchangeability of biosimilars. It also focuses on comparability tests in the manufacturing processes of biologic products. The book covers all of the statistical issues that may occur in biosimilar studies under various study designs at different stages of research and development of biologic products.

Randomized phase II cancer clinical trials are increasingly being used in recent years because of lower sample size requirements when multiple treatments are being evaluated. This accessible book covers both the latest developments in methodology as well as traditional single-arm phase II trial methods. It keeps the statistical level at a minimum so that both statisticians and clinicians conducting phase II clinical trials understand the material. The book includes many diverse statistical designs and analysis methods relevant to oncology.

• Represents the first book on biosimilarity of drugs and biologic products • Evaluates various criteria for assessing biosimilar products • Presents the totality biosimilarity index, a general approach for assessing biosimilarity • Examines study designs for switching or alternating drug interchangeability

Selected Contents:

• Reviews the statistical methods for single-arm phase II trials • Presents flexible clinical trial designs

Selected Contents:

Introduction. Bioequivalence Experience for Drug Products. Regulatory Requirement for Assessing Follow-on Biologics. Criteria for Similarity. Statistical Methods for Assessing Average Biosimilarity. General Approach for Assessing Biosimilarity. Non-Inferiority versus Equivalence. Assessment of Biosimilarity in Variability. Impact of Variability on Biosimilarity Limits for Assessing Follow-on Biologics. Drug Interchangeability. CMC Requirements for Biological Products. Test for Comparability in Manufacturing Process. Stability Analysis. Current Issues in Biosimilar Studies. References. Index.

Catalog no. K16860, August 2013, c. 424 pp.

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

• Provides diverse statistical design and analysis methods for randomized phase II trials in oncology

Introduction. Single-Arm Phase II Trial Designs.

Inference on the Binomial Probability in Single-Arm Multistage Clinical Trials. Single-Arm Phase II Clinical Trials with Time-to-Event Endpoints. Single-Arm Phase II Trials with Heterogeneous Patient Populations. Randomized Phase II Trials for Selection: No Prospective Control Arms. Randomized Phase II Cancer Clinical Trials with a Prospective Control on Binary Endpoints (I): Two-Sample Binomial Test.

Randomized Phase II Cancer Clinical Trials with a Prospective Control on Binary Endpoints (II): Fisher Exact Test. Randomized Phase II Trials with Heterogeneous Patient Populations: Stratified Fisher’s Exact Test. Randomized Phase II Clinical Trials Based on Survival Endpoints: Two-Sample Logrank Test.

Some Flexible Phase II Clinical Trial Designs.

Catalog no. K13295, May 2013, 230 pp.

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

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Biostatistics and Epidemiology IntervalCensored Timeto-Event Data Methods and Applications Edited by

Joint Models for Longitudinal and Time-toEvent Data With Applications in R

Ding-Geng (Din) Chen, Jianguo Sun, and Karl E. Peace

Dimitris Rizopoulos

A practical guide for biomedical researchers, clinicians, biostatisticians, and graduate students in biostatistics, this volume covers the latest developments in the analysis and modeling of interval-censored time-toevent data. Top researchers from academia, biopharmaceutical industries, and government agencies show how up-to-date statistical methods are used in real biopharmaceutical and public health applications.

• Provides up-to-date methodologies for intervalcensored time-to-event data

Longitudinal studies often investigate how a marker that is repeatedly measured in time is associated with an event of interest, such as prostate cancer studies where longitudinal PSA level measurements are collected in conjunction with the time-to-recurrence.

This book provides a full treatment of joint models for longitudinal and time-to-event data. Emphasizing applications, the content is explanatory rather than mathematically rigorous. All illustrations are available in the R programming language via the author’s freely available JM package.

• Offers easy access to computational methods and R software packages

• Provides a complete treatment of joint models for longitudinal and time-to-event data

• Presents data from actual clinical trials and biomedical research, including breast cancer and HIV data sets

• Introduces various extensions of the standard joint model, including several parameterizations for the association structure and the handling of competing risks

• Formulates statistical analysis plans associated with real-world clinical data

Selected Contents: Introduction and Overview: Overview of Recent Developments for Interval-Censored Data. A Review of Various Models for Interval-Censored Data.

Methodology: Current Status Data in the TwentyFirst Century. Regression Analysis for Current Status Data. Statistical Analysis of Dependent Current Status Data. Bayesian Semiparametric Regression Analysis of Interval-Censored Data with Monotone Splines.

Bayesian Inference of Interval-Censored Survival Data. Targeted Minimum Loss-Based Estimation of a Causal Effect Using Interval-Censored Time-to-Event Data. Consistent Variance Estimation in IntervalCensored Data. Applications and Related Software: Bias Assessment in Progression-Free Survival Analysis. Bias and Its Remedy in IntervalCensored Time-to-Event Applications. Adaptive Decision Making Based on Interval-Censored Data in a Clinical Trial to Optimize Rapid Treatment of Stroke. Practical Issues on Using Weighted Logrank Tests. glrt—New R Package for Analyzing IntervalCensored Survival Data. Index.

Erasmus University Medical Center, Rotterdam, Netherlands

• Covers several diagnostic tools based on residuals to assess the assumptions behind a joint model • Discusses dynamic predictions for survival and longitudinal outcomes as well as discrimination concepts for longitudinal markers • Emphasizes applications so readers understand the type of research questions best answered with joint models

Selected Contents: Introduction. Analysis of Longitudinal Data. Analysis of Time-to-Event Data. Joint Models for Longitudinal and Time-to-Event Data. Extensions of the Standard Joint Model. Diagnostics. Survival Probabilities and Prospective Accuracy Measures.

Catalog no. K13371, June 2012, 275 pp.

ISBN: 978-1-4398-7286-4, $79.95 / £49.99 Also available as an eBook

Catalog no. K14515, July 2012, 433 pp.

ISBN: 978-1-4665-0425-7, $99.95 / £63.99 Also available as an eBook

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

15

Biostatistics and Epidemiology Coming soon!

Handbook of Survival Analysis Edited by

John P. Klein, Joseph G. Ibrahim, Thomas Scheike, and Johannes C. van Houwelingen This handbook focuses on the analysis of lifetime data arising from the biological and medical sciences. It deals with semiparametric and nonparametric methods. For investigators new to this field, the book provides an overview of the topic along with examples of the methods discussed. It presents both classical methods and modern Bayesian approaches to the analysis of data.

Catalog no. K15384, August 2013, c. 656 pp.

ISBN: 978-1-4665-5566-2, $99.95 / £63.99

Multivariate Survival Analysis and Competing Risks Martin J. Crowder 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, $99.95 / £63.99 Also available as an eBook

Coming soon!

Survival Analysis in Medicine and Genetics

Dynamic Prediction in Clinical Survival Analysis

Jialiang Li National University of Singapore

Shuangge Ma Yale University, New Haven, Connecticut, USA

This text introduces up-to-date statistical methods for survival data analysis in medicine and genetics. Along with classical results, it presents new developments in interval censoring, statistical diagnostics with timedependent outcomes, analysis of ultrahigh-dimensional data sets, cure rate models, and repeated measure data. Suitable for both graduate students and biomedical researchers, the text covers applications in cancer studies, medical diagnosis, genetics, and genomics. It provides R code and example data sets online.

Catalog no. K14175, June 2013, c. 384 pp.

ISBN: 978-1-4398-9311-1, $99.95 / £63.99

Hans 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. Written by one of the pioneers in the area, this book synthesizes these developments in a unified framework. It covers a range of models, including 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, $93.95 / £59.99 Also available as an eBook

Also available as an eBook

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Biostatistics and Epidemiology

Coming soon!

Bayesian Methods in Epidemiology Lyle D. Broemeling

Handbook of Statistics in Clinical Oncology Third Edition Edited by

John Crowley

Broemeling and Associates, Medical Lake, Washington, USA

Cancer Research and Biostatistics, Seattle, Washington, USA

A valuable reference for epidemiologists, biostatisticians, and graduate students, this book presents an introduction to epidemiology that uses Bayesian statistical methods to explore the association between disease and risk. It includes a brief introduction to the concepts of epidemiology, the basic elements of Bayesian statistics, and the types of epidemiologic studies that can be analyzed by Bayesian methods. For each problem in epidemiology, the Bayesian analysis is derived and explained.

Antje Hoering

Catalog no. K16074, August 2013, c. 392 pp.

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

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

Addressing the many challenges that have arisen since the publication of its predecessor, this third edition covers the newest developments involved in the design and analysis of cancer clinical trials. Accessible to statisticians in clinical trials as well as oncologists interested in clinical trial methodology, this edition contains numerous figures and examples to better explain concepts. New topics in this edition include trial designs for targeted agents, Bayesian trial design, and the inclusion of high-dimensional data and imaging techniques.

Catalog no. K12872, March 2012, 657 pp.

ISBN: 978-1-4398-6200-1, $119.95 / £76.99 Also available as an eBook

Clinical Trials in Oncology Third Edition Stephanie Green, Jacqueline Benedetti, Angela Smith, and John Crowley The new edition of this bestseller provides a nontechnical and thoroughly up-to-date 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 trials 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, $99.95 / £63.99

Statistics of Medical Imaging Tianhu Lei Physical principles and mathematical procedures of medical imaging technologies have been extensively studied during past decades. However, less work has been done on their statistical aspect. Filling this gap, this book provides a theoretical framework for statistical investigation into medical technologies. Rather than offer detailed statistical descriptions of basic imaging protocols of x-ray CT and MRI, the book presents a method to conduct similar statistical investigations into more complicated imaging protocols.

Catalog no. C8842, December 2011, 438 pp.

ISBN: 978-1-4200-8842-7, $99.95 / £63.99 Also available as an eBook

Also available as an eBook

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

17

Biostatistics and Epidemiology Coming soon!

Coming soon!

Statistical and Computational Methods in Brain Image Analysis Moo K. Chung A major challenge in brain mapping is caused by the massive amount of nonstandard high-dimensional data that is difficult to analyze using standard techniques. This book covers modern statistical and computational techniques for analyzing such data.

Methodological topics covered include finite mixture models, logistic models, nonparametric regression, mixed effects models, neural networks, and support vector machines. Real data sets are used to illustrate the methods and MATLAB® code is available online to implement them.

• Presents a coherent statistical and mathematical treatment of methods useful in neuroimaging applications

Applied MetaAnalysis with R Ding-Geng 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 a thorough presentation of meta-analysis for clinical trial data with detailed step-by-step illustrations on implementation in R. The examples are based on the actual experiences of the authors in many areas of clinical drug development.

Real examples of clinical trials are presented and after understanding the application, the various clinical trial methods inherent in the clinical trials are identified.

The book’s presentation reflects a case study approach.

• Represents one of the first books on metaanalysis with R • Describes real clinical trials with the associated clinical data

• Includes real examples and case studies from top journals

• Provides a step-by-step approach to using R for analysis

• Emphasizes image visualization using MATLAB

• Offers data and R code available for download online

• Offers all of the brain imaging data and codes from the text available for download on the author’s website

Selected Contents: Introduction to Brain and Medical Images. Bernoulli Models for Binary Images. General Linear Models.

Gaussian Kernel Smoothing. Random Fields Theory.

Anisotropic Kernel Smoothing. Multivariate General Linear Models. Cortical Surface Analysis. Heat Kernel Smoothing on Surfaces. Cosine Series Representation of 3D Curves. Weighted Spherical Harmonic Representation. Multivariate Surface Shape Analysis.

Laplace-Beltrami Eigenfunctions for Surface Data.

Persistence Homology. Sparse Networks. Sparse Shape Models. Modeling Structural Brain Networks.

Mixed Effect Models. Bibliography.

Selected Contents: Introduction to R. Research Protocol for MetaAnalyses. Meta-Analysis for Continuous Data. MetaAnalysis of Categorical Data. Fixed-Effect MetaAnalysis Models. Random-Effect Meta-Analysis Models. Quantifying Heterogeneity in Meta-Analysis.

Meta Regression. Subgroup Analysis. Publication Biases in Meta-Analysis. Meta-Analysis of a Multicenter Clinical Trial. References. Indices.

Catalog no. K14600, June 2013, c. 344 pp.

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

Catalog no. K11644, July 2013, c. 416 pp.

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

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Biostatistics and Epidemiology New!

Regression Models as a Tool in Medical Research Werner Vach Institute of Medical Biometry and Medical Informatics, Freiburg, Germany

While regression models have become standard tools in medical research, understanding how to properly apply the models and interpret the results is often challenging for beginners. This text presents the fundamental concepts and important aspects of regression models most commonly used in medical research, including the classical regression model for continuous outcomes, the logistic regression model for binary outcomes, and the Cox proportional hazards model for survival data. The author emphasizes adequate use, correct interpretation of results, appropriate presentation of results, and avoidance of potential pitfalls.

Catalog no. K15111, November 2012, 495 pp.

ISBN: 978-1-4665-1748-6, $89.95 / £57.99

Applied Medical Statistics Using SAS Geoff Der University of Glasgow, Scotland, UK

Brian S. Everitt King’s College, London, UK (Retired)

“The book would make an excellent reference guide for medical data analysts with access to base SAS 9.3 or a textbook for an introductory and intermediate graduate biostatistics course. … The thoroughness of procedures and the consideration the authors included in the selection of graphs, SAS code, and theory allow this book to be a resourceful companion for medical analysts. If looking for a broad selection of medical analyses using base SAS 9.3, this is the book for you … .”

—Journal of Statistical Software, January 2013

Catalog no. K13087, October 2012, 559 pp.

ISBN: 978-1-4398-6797-6, $89.95 / £57.99 Also available as an eBook

Also available as an eBook

New!

Bayesian Methods in Health Economics Gianluca Baio

Computational Systems Biology of Cancer Emmanuel Barillot, Laurence Calzone, Philippe Hupe, Jean-Philippe Vert, and Andrei Zinovyev

University College London, UK

Institut Curie, Paris, France

Health economics is concerned with the study of the cost-effectiveness of health care interventions. This book provides an overview of Bayesian methods for the analysis of health economic data. After an introduction to the basic economic concepts and methods of evaluation, it presents Bayesian statistics using minimal mathematics. It describes cost-effectiveness analysis from a statistical viewpoint and Bayesian computation. Case studies cover cost-effectiveness analyses of anti-asthma treatment, influenza vaccination and cardiovascular treatment. Data sets and WinBUGS and JAGS code are available online.

“An up-to-date, comprehensive and very readable overview, this book has plenty for everyone interested in computational systems biology of cancer.

Almost all important topics are introduced and explained, and pointers are given to further work.

The bibliography is outstanding. Think of this as your guide book to the field, as well as a way to get started in it.”

Catalog no. K14236, November 2012, 243 pp.

ISBN: 978-1-4398-9555-9, $89.95 / £57.99

Catalog no. K11531, August 2012, 461 pp.

ISBN: 978-1-4398-3144-1, $79.95 / £49.99

—Terry Speed, University of California, Berkeley, and Walter and Eliza Hall Institute of Medical Research, Melbourne

Also available as an eBook

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

19

Biostatistics and Epidemiology / Computational Statistics Coming soon!

Methods of Statistical Model Estimation

Medical Biostatistics

Joseph M. Hilbe California Institute of Technology, Pasadena, and Arizona State University, Tempe, USA

Third Edition Abhaya Indrayan The third edition of this acclaimed reference focuses on the statistical aspects of medicine with a medical perspective, showing how biostatistics is a useful tool to manage some medical uncertainties. This edition includes several new topics, provides expanded coverage of many other topics and includes software illustrations. The author presents step-by-step explanations of statistical methods with the help of numerous real-world examples. Guide charts at the beginning of the book enable quick access to the relevant statistical procedure.

Catalog no. K13952, August 2012, 1024 pp.

ISBN: 978-1-4398-8414-0, $129.95 / £82.00 Also available as an eBook

Andrew P. Robinson University of Melbourne, Parkville, Australia

In many situations, standard statistical models may not be suitable for the data being studied; the researcher will need to construct a model that will provide appropriate parameter estimates. This book provides a step-by-step guide to estimating regression models using optimization, maximum likelihood, quadrature, and simulation. The text allows readers to develop their own R code for models relevant to the data they are studying. It begins with background material and basic models, building through to more complex situations, such as mixed effects models. It contains data from various disciplines, illustrating how the techniques can be applied to building models for real data problems.

• Provides a step-by-step guide to model estimation using R • Covers the four primary methods: optimization, maximum likelihood, quadrature, and simulation

Coming soon!

Optimal Design for Nonlinear Response Models Valerii V. Fedorov GlaxoSmithKline, Collegeville, Pennsylvania, USA

Sergei L. Leonov AstraZeneca, Wilmington, Delaware, USA

This book examines the theory of optimal modelbased design and provides examples of optimal designs for various models, mostly related to biopharmaceutical applications. The authors pay special attention to adaptive or sequential optimal designs for nonlinear regression models when estimation and optimal design are performed in stages. The text illustrates the designs using an application of a first-order optimization algorithm in the space of information matrices, which is implemented in both MATLAB® and SAS.

• Includes background on modeling and builds from basic models to more complex setups • Develops readers’ R skills • Contains many real data examples to illustrate the methods

Selected Contents: R as a Modeling Language. Overview of Model Estimation. Constructing Synthetic Models.

Estimation of Gaussian Models. Optimization.

Maximum Likelihood Estimation. Estimation Using Quadrature. Estimation Using Simulation. Selecting the Optimal Method of Estimation.

Catalog no. K12707, June 2013, c. 256 pp.

ISBN: 978-1-4398-5802-8, $89.95 / £57.99 Also available as an eBook

Catalog no. K11140, June 2013, c. 404 pp.

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

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Computational Statistics Programming Graphical User Interfaces in R Michael Lawrence Genentech Research and Early Development, South San Francisco, California, USA

The R Primer

John Verzani

Claus Thorn Ekstrøm

CUNY/College of Staten Island, New York, USA

University of Copenhagen, Frederiksberg, Denmark

Focusing on GUIs within the R language, this book shows programmers and users how to develop their own GUIs, enabling them to interface with other languages. The text opens the possibilities of R’s huge and growing set of statistical methods. The authors cover four different packages for writing GUIs: gWidgets, RGtk2, Qt, and Tcl Tk. Supported by a package in CRAN that contains all of the code along with additional examples, the text is filled with numerous examples ranging from the very simple to detailed illustrations of how to code actual interfaces.

“This book provides a good introduction to R, using a clear layout and detailed, reproducible examples.

An ideal tool for any new R user. … A wide range of topics are covered, making the book suitable for a variety of readers, from undergraduate students to professionals new to R. … an extremely helpful introduction to a very useful statistical package.”

Catalog no. K12672, June 2012, 479 pp.

ISBN: 978-1-4398-5682-6, $79.95 / £49.99

—Claire Keeble, Journal of Applied Statistics, 2012

Catalog no. K12876, August 2011, 299 pp.

Soft Cover ISBN: 978-1-4398-6206-3, $39.95 / £26.99 Also available as an eBook

Also available as an eBook

Statistical Computing in C++ and R Randall L. Eubank Arizona State University, Tempe, USA

Ana Kupresanin Lawrence Livermore National Laboratory, California, USA

This book discusses code development in C++ and R, before going beyond to look at the valuable use of these two languages in unison. It covers linear equation solution with regression and linear models motivation, optimization with maximum likelihood and nonlinear least squares motivation, and random number generation. While the text does require a working knowledge of basic concepts in statistics and experience in programming, it does not require knowledge specific to C++ or R. Catalog no. C6650, December 2011, 556 pp.

ISBN: 978-1-4200-6650-0, $89.95 / £59.99 Also available as an eBook

New!

Handbook of SAS® DATA Step Programming Arthur Li City of Hope National Medical Center, Los Angeles County, California, USA

This handbook shows readers how best to manage and manipulate data by using the DATA step in SAS, helping them avoid common problems when creating SAS data sets. The author explains that learning syntax does not solve all problems; rather, a thorough comprehension of SAS processing is needed for successful programming. He also guides readers through a programming task. In most of the examples, the author first presents strategies and steps for solving the problem, then offers a solution, and finally gives a more detailed explanation of the solution.

Catalog no. K15213, April 2013, 275 pp.

ISBN: 978-1-4665-5238-8, $59.95 / £38.99 Also available as an eBook

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

21

Computational Statistics Data Analysis Using Stata Third Edition

New!

Ulrich Kohler Social Science Research Center, Berlin, Germany

Frauke Kreuter University of Maryland, College Park, USA

A comprehensive introduction to both statistical methods and Stata, this text helps beginners learn the logic of data analysis and interpretation and easily become self-sufficient data analysts. It also offers tips and tricks for readers already familiar with Stata. Step by step, the book leads readers through the entire process of data analysis, covering the principles of Stata, data manipulation, graphical representation, and programs to automate repetitive tasks. This third edition also explores advanced topics such as standard errors in complex survey and multiple imputation.

Catalog no. N10727, August 2012, 497 pp.

Soft Cover ISBN: 978-1-59718-110-5, $79.95 / £49.99

Sean Becketti This work provides a step-by-step guide to essential time series techniques, from the incredibly simple to the quite complex. At the same time, the book demonstrates how these techniques can be applied in Stata. It emphasizes an understanding of the intuition underlying theoretical innovations and an ability to apply them. Real-world examples illustrate the application of each concept as it is introduced. The author also highlights the pitfalls as well as the power of each new tool.

Catalog no. N10838, January 2013, 741 pp.

Soft Cover ISBN: 978-1-59718-132-7, $79.95 / £49.99

A Visual Guide to Stata Graphics

A Gentle Introduction to Stata Revised Third Edition Alan C. Acock

Third Edition Michael N. Mitchell UCLA Academic Technology Services Consulting Group, Los Angeles, California, USA

Oregon State University, Corvallis, USA

Updated to reflect the new features of Stata 11, this third edition continues to help new Stata users become proficient in Stata. This edition includes a new chapter on the analysis of missing data and the use of multiple-imputation methods. It also provides an extensive revision of the chapter on ANOVA, along with additional material on the application of power analysis. Each chapter includes exercises and real data sets are used throughout.

Catalog no. N10594, March 2012, 401 pp.

Soft Cover ISBN: 978-1-59718-109-9, $79.95 / £49.99

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Introduction to Time Series Using Stata

With over 900 illustrated examples and quick-reference tabs, this edition helps readers quickly create and customize high-quality graphs for any type of statistical data. Each graph is displayed in color with simple and clear instructions that illustrate how to create and customize graphs using either Stata commands or the Stata Graph Editor. Stata’s powerful graphics system gives readers complete control over how the elements of the graph look, from marker symbols to lines, from legends to captions and titles, from axis labels to grid lines, and more.

Catalog no. N10565, January 2012, 499 pp.

Soft Cover ISBN: 978-1-59718-106-8, $89.95 / £57.99

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Computational Statistics / Statistical Learning and Data Mining Interpreting and Visualizing Regression Models Using Stata Michael N. Mitchell UCLA Academic Technology Services Consulting Group, Los Angeles, California, USA

New!

Support Vector Machines Optimization Based Theory, Algorithms, and Extensions Naiyang Deng, Yingjie Tian, and Chunhua Zhang

This book presents a clear treatment of how to carefully present results from model-fitting in a wide variety of settings. It is indispensable to anyone who has to present the tangible meaning of a complex model in a clear fashion, regardless of the audience. For example, many experienced researchers start to squirm when asked to give a simple explanation of the applied meaning of interactions in nonlinear models such as logistic regression. The tools in this book make this task much more enjoyable and comprehensible.

“This book provides a concise overview of SVMs, starting from the basics and connecting to many of their most significant extensions. Starting from an optimization perspective provides a new way of presenting the material, including many of the technical details that are hard to find in other texts. And since it includes a discussion of many practical issues important for the effective use of SVMs (e.g., feature construction), the book is valuable as a reference for researchers and practitioners alike.”

Catalog no. N10624, April 2012, 558 pp.

Soft Cover ISBN: 978-1-59718-107-5, $79.95 / £49.99

Catalog no. K12703, December 2012, 363 pp.

ISBN: 978-1-4398-5792-2, $89.95 / £57.99

—Thorsten Joachims, Cornell University

Also available as an eBook

Multilevel and Longitudinal Modeling Using Stata Volumes I and II, Third Edition Sophia RabeHesketh

Ensemble Methods

University of California, Berkeley, USA

Foundations and Algorithms

Anders Skrondal

Zhi-Hua Zhou

London School of Economics, UK

Nanjing University, China

This book examines Stata’s treatment of generalized linear mixed models, also known as multilevel or hierarchical models. Volume I covers continuous Gaussian linear mixed models. Volume II discusses generalized linear mixed models for binary, categorical, count, and survival outcomes.

“Professor Zhou’s book is a comprehensive introduction to ensemble methods in machine learning.

It reviews the latest research in this exciting area.

I learned a lot reading it!”

Catalog no. N10560, April 2012, Soft Cover, Set ISBN: 978-1-59718-108-2, $149.95 / £95.00 Volume I: Continuous Responses Catalog no. N10561, April 2012, Soft Cover, 514 pp.

ISBN: 978-1-59718-103-7, $89.95 / £57.99 Volume II: Categorical Responses, Counts, and Survival Catalog no. N10563, April 2012, Soft Cover, 484 pp.

ISBN: 978-1-59718-104-4, $89.95 / £57.99

—Thomas G. Dietterich, Oregon State University, ACM Fellow, and Founding President of the International Machine Learning Society

“This is a timely book. Right time and right book … with an authoritative but inclusive style that will allow many readers to gain knowledge on the topic.”

—Fabio Roli, University of Cagliari

Catalog no. K11467, June 2012, 236 pp.

ISBN: 978-1-4398-3003-1, $79.95 / £49.99 Also available as an eBook

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

23

Statistical Learning and Data Mining / Statistics for Business, Finance, and Economics Economic Time Series

Clustering A Data Recovery Approach, Second Edition

Modeling and Seasonality

Boris Mirkin

Edited by

DCS Birkbeck University of London, UK, and NRU Higher School of Economics, Moscow, Russia

William R. Bell, Scott H. Holan, and Tucker S. McElroy

Covering both classical and modern approaches, including k-means and divisive clustering, this book uses in-depth case studies to illustrate how clustering methods can be applied. Along with expanded and improved case studies, this second edition presents new material on variable selection and weighting, similarity/relational data clustering, spectral clustering, and interpretation of clusters. A supporting website provides MATLAB® code and data sets for all of the examples presented in the text.

“The list of authors includes some of the leading contributors to the literature … All chapters contain both theoretical development and also empirical applications to economic series. … an ideal reference for those interested in recent developments in this literature.”

Catalog no. K11742, October 2012, 374 pp.

ISBN: 978-1-4398-3841-9, $99.95 / £63.99 Also available as an eBook

—Alastair R. Hall, Journal of Times Series Analysis, June 2012

This practical volume covers frequency domain properties of signal extraction filters, the Akaike Information Criterion and model selection criteria, diagnostics for seasonal adjustment, calendar adjustments of seasonal time series, generalized airline models for modeling seasonality, and much more.

Catalog no. K12089, March 2012, 554 pp.

ISBN: 978-1-4398-4657-5, $99.95 / £63.99 Also available as an eBook

New!

Risk Assessment and Decision Analysis with Bayesian Networks Norman Fenton and Martin Neil Queen Mary University of London, UK

“The book provides sufficient motivation and examples (as well as the mathematics and probability where needed from scratch) to enable readers to understand the core principles and power of Bayesian networks. However, the focus is on ensuring that readers can build practical Bayesian network models … readers are provided with a tool that performs the propagation, so they will be able to build their own models to solve real-world risk assessment problems.”

—Judea Pearl, UCLA Computer Science Department and 2011 Turing Award winner

Catalog no. K10450, November 2012, 524 pp.

ISBN: 978-1-4398-0910-5, $79.95 / £41.99

24

Quantitative Operational Risk Models Catalina Bolancé, Montserrat Guillén, Jim Gustafsson, and Jens Perch Nielsen Presenting a nonparametric approach to modeling operational risk data, this book offers a practical perspective that combines statistical analysis and management orientations. It covers the statistical theory prerequisites and summarizes important contributions made in the past decade. The authors explain how to implement the new density estimation methods for analyzing the loss distribution in operational risk for banks and insurance companies. They also include SAS and R routines to implement all of the procedures discussed in the text.

Catalog no. K14258, February 2012, 236 pp.

ISBN: 978-1-4398-9592-4, $79.95 / £44.99 Also available as an eBook

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Statistics for Business, Finance, and Economics Stochastic Processes with Applications to Finance

New!

Masaaki Kijima

Statistical Methods for Financial Engineering

Tokyo Metropolitan University, Japan

Bruno Rémillard HEC Montreal, Quebec, Canada

Suitable for graduate students and professionals in financial engineering, operations research, and mathematical and statistical finance, this updated new edition presents an accessible treatment of the theory of discrete stochastic processes and their applications in finance. By presenting important results in discrete processes and showing how to transfer those results to their continuous counterparts, the text imparts an intuitive and practical understanding of the subject. It thoroughly explores applications to the pricing of derivative securities, corporate bonds, and credit derivatives.

While many financial engineering books are available, the statistical aspects behind the implementation of stochastic models used in the field are often overlooked or restricted to a few well-known cases. This self-contained book guides current and future practitioners on implementing the most useful stochastic models used in financial engineering. Each chapter introduces powerful and practical statistical tools necessary to implement the models. Throughout the text, examples using MATLAB® illustrate the application of the techniques to solve real-world financial problems.

MATLAB and R programs are available on the author’s website.

Second Edition

Catalog no. K13980, May 2013, 336 pp.

ISBN: 978-1-4398-8482-9, $89.95 / £57.99 Also available as an eBook

Catalog no. K12677, April 2013, c. 496 pp.

ISBN: 978-1-4398-5694-9, $89.95 / £57.99 Also available as an eBook

New!

Random Dynamical Systems in Finance Anatoliy Swishchuk University of Calgary, Alberta, Canada

Shafiqul Islam University of Prince Edward Island, Charlottetown, Canada

This book provides a variety of RDS for approximating financial models, presents numerous option pricing formulas for these models, and studies the stability and optimal control of RDS. Through numerous examples, the authors explain how the theory of RDS can describe the asymptotic and qualitative behavior of systems of random and stochastic differential/difference equations in terms of stability, invariant manifolds, and attractors. They also develop techniques for implementing RDS as approximations to financial models and option pricing formulas.

Catalog no. K13017, April 2013, c. 349 pp.

ISBN: 978-1-4398-6718-1, $99.95 / £63.99

New!

A Course on Statistics for Finance Stanley L. Sclove University of Illinois, Chicago, USA

This text presents statistical methods for financial investment analysis. Providing the connection between elementary statistics courses and quantitative finance courses, the book helps both existing and future quants improve their data analysis skills and better understand the modeling process. It incorporates applied statistics and mathematical statistics and requires no prior background in finance. The author introduces regression analysis, time series analysis, and multivariate analysis step by step using models and methods from finance.

Catalog no. K14149, December 2012, 269 pp.

ISBN: 978-1-4398-9254-1, $89.95 / £57.99 Also available as an eBook

Also available as an eBook

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

25

Statistics for Business, Finance, and Economics New!

Computational Methods in Finance

Getting Started with Business Analytics Insightful DecisionMaking

Ali Hirsa

David Roi Hardoon

Caspian Capital Management, LLC, New York, USA

SAS, Singapore

Galit Shmueli

“A natural polymath, the author is at once a teacher, a trader, a quant, and now an author of a book for the ages. The content reflects the author’s vast experience teaching master’s level courses at Columbia and NYU, while simultaneously researching and trading on quantitative finance in leading banks and hedge funds.”

Indian School of Business, Hyderabad

—Peter Carr, Morgan Stanley and NYU Courant Institute of Mathematical Sciences

Catalog no. K11454, September 2012, 444 pp.

ISBN: 978-1-4398-2957-8, $89.95 / £59.99 Also available as an eBook

“… a good summary of the analytical solutions employed across these industries today, including an updated vocabulary on new domains such as social media. … Looking back at my career in the field of business analytics, I realize that it would have been extremely helpful to have had such a book in hand.

It would have provided me with guidance on structuring my analytical solutions and would have inspired me to greater creativity. I hope this book will light the spark of curiosity for a new generation of data scientists.”

—Eric Sandosham, Citibank, Asia Pacific 2010–2012

Catalog no. K14271, March 2013, 190 pp.

ISBN: 978-1-4398-9653-2, $59.95 / £38.99

Customer and Business Analytics An Introduction to Exotic Option Pricing Peter Buchen University of Sydney, Australia

“The book presents an entertaining and captivating course in option pricing, aiming to derive closed form analytical formulas for the prices of exotic options in an elegant way, provided such a formula exists. Thanks to the machinery developed by the author and his work group, pricing formulas for even the most complex exotic options are obtained from elementary pricing formulas using elegant arguments and simple algebraic manipulations, i.e. without lengthy integrations. … a very valuable treatise on exotic option pricing …”

—Tamás Mátrai, Zentralblatt MATH 1242

Catalog no. C9100, February 2012, 296 pp.

ISBN: 978-1-4200-9100-7, $79.95 / £49.99 Also available as an eBook

26

Applied Data Mining for Business Decision Making Using R Daniel S. Putler Alteryx, California, USA

Robert E. Krider Simon Fraser University, Burnaby, British Columbia, Canada

Showing how data mining can improve the performance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities. It explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. The authors also give insight into some of the challenges faced when deploying these tools.

Catalog no. K14501, May 2012, 315 pp.

Soft Cover ISBN: 978-1-4665-0396-0, $69.95 / £44.99 Also available as an eBook

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Statistics for the Social and Behavioral Sciences Coming soon!

Incomplete Categorical Data Design Non-Randomized Response Techniques for Sensitive Questions in Surveys Guo-Liang Tian The University of Hong Kong

Man-Lai Tang Hong Kong Baptist University

This book presents new techniques designed to overcome the bias inherent in posing sensitive questions in sociological or behavioral science surveys, without requiring a means of randomization. The authors provide a systematic introduction to NRR techniques that can overcome the limitations of RR techniques, combining the strengths of existing approaches, such as RR models, incomplete data design, expectationmaximization algorithm, data augmentation algorithm, and the bootstrap method. R codes are provided for implementing the methods.

A Statistical Guide for the Ethically Perplexed Lawrence Hubert University of Illinois at UrbanaChampaign, USA

Howard Wainer National Board of Medical Examiners, Pennsylvania, USA

“Using all the resources provided, one can assemble a very long list of issues and applications, with readings and references. … recommended … a resource the statistically sophisticated teacher can mine for material from which to create their own examples to engage students.”

—Robert W. Hayden, MAA Review, December 2012

“A valuable guide for sorting through ethical issues in the behavioral, social, and biomedical sciences.”

—C.K. Gunsalus, National Center for Professional and Research Ethics and University of Illinois at Urbana-Champaign

Catalog no. K12579, July 2013, c. 230 pp.

ISBN: 978-1-4398-5533-1, $89.95 / £57.99

Catalog no. K13412, September 2012, 588 pp.

Soft Cover ISBN: 978-1-4398-7368-7, $49.95 / £31.99

Also available as an eBook

Also available as an eBook

Latent Markov Models for Longitudinal Data

Event History Analysis with R

Francesco Bartolucci, Alessio Farcomeni, and Fulvia Pennoni

Göran Broström Professor Emeritus, Umeå University, Sweden

Drawing on the authors’ extensive research in the analysis of categorical longitudinal data, this book focuses on the formulation of latent Markov models and the practical use of these models. It demonstrates how to use the models in three types of analysis, with numerous examples illustrating how latent Markov models are used in economics, education, sociology, and other fields. The R and MATLAB® routines used for the examples are available on the authors’ website.

With an emphasis on social science applications, this book presents an introduction to survival and event history analysis. It includes a wide range of real examples, with data available online and supported by a dedicated R package for performing all of the analyses. Keeping mathematical details to a minimum, the author covers both discrete and continuous time data, parametric proportional hazards, and accelerated failure times.

Catalog no. K10884, October 2012, 252 pp.

ISBN: 978-1-4398-1708-7, $89.95 / £57.99

Catalog no. K11534, April 2012, 236 pp.

ISBN: 978-1-4398-3164-9, $79.95 / £49.99 Also available as an eBook

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

27

Statistics for the Social and Behavioral Sciences / Environmental Statistics New!

Informative Hypotheses Theory and Practice for Behavioral and Social Scientists Herbert Hoijtink University Utrecht, The Netherlands

Data Analysis and Statistics for Geography, Environmental Science, and Engineering Miguel F. Acevedo

This detailed book discusses the evaluation of behavioral and social science hypotheses that are more informative than traditional null and alternative hypotheses. Requiring a minimal prerequisite knowledge of multivariate statistics, such as regression and ANOVA, it provides relevant information for active researchers in the social and behavioral sciences. The book considers Bayesian and classical approaches, pays considerable attention to sample size determination, and provides software for all functions discussed.

Catalog no. K13785, October 2011, 241 pp.

ISBN: 978-1-4398-8051-7, $83.95 / £52.99 Also available as an eBook

University of North Texas, Denton, USA

This practical, classroom-tested book helps readers learn quantitative methodology, including how to implement advanced analysis methods using an open-source software platform. The author brings together principles of statistics and probability, multivariate analysis, and spatial analysis methods applied to a variety of geographical and environmental models. Theory is accompanied by hands-on computer exercises, progressing from easy to difficult. The text also presents a review of mathematical methods, making the book self-contained.

Catalog no. K13985, December 2012, 557 pp.

ISBN: 978-1-4398-8501-7, $99.95 / £63.99 Also available as an eBook

Coming soon!

Agricultural Statistical Data Analysis Using Stata

Quantitative Ecotoxicology Second Edition Michael C. Newman

George Boyhan University of Georgia, Athens, USA

College of William and Mary, Gloucester Point, Virginia, USA

Stata is one of the most widely used statistical analysis software packages for investigating experimental design and analysis in agricultural research. Easy to read and user friendly for beginners, this book provides an introduction to Stata and its use in agricultural research. It opens with a general discussion of statistical software and then covers data entry and applications of Stata. More advanced topics include the use of Stata in regression analysis and in analyzing data that is typically not normally distributed.

“Mike Newman’s Quantitative Ecotoxicology provides a unique and much-needed addition to the ecotoxicological literature. He covers the most important ecotoxicological concepts (bioaccumulation, lethal and nonlethal responses to stress at the individual level, population and metapopulation effects, and community effects) and effectively combines these with the appropriate quantitative options and considerations for assessing these processes. This book is like an ecotoxicology text and statistics text rolled into one.”

Catalog no. K20263, June 2013, c. 264 pp.

Soft Cover ISBN: 978-1-4665-8585-0, $79.95 / £49.99 Also available as an eBook

—Valery E. Forbes, University of Nebraska-Lincoln

Catalog no. K11602, August 2012, 592 pp.

ISBN: 978-1-4398-3564-7, $149.95 / £95.00 Also available as an eBook

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Environmental Statistics Introduction to Hierarchical Bayesian Modeling for Ecological Data Eric Parent ENGREF/AgroParisTech, France

Etienne Rivot Agrocampus Ouest, INRA, Rennes, France

Making statistical modeling and inference more accessible to ecologists and related scientists, this book gives readers a flexible and effective framework to learn about complex ecological processes from various sources of data. It shows how Bayesian statistical modeling provides an intuitive way to organize data, test ideas, investigate competing hypotheses, and assess degrees of confidence of predictions. Data sets, exercises, and R and WinBUGS codes are available on the authors’ website.

Catalog no. C9195, August 2012, 427 pp.

ISBN: 978-1-58488-919-9, $89.95 / £57.99 Also available as an eBook

Simulating Nature A Philosophical Study of ComputerSimulation Uncertainties and Their Role in Climate Science and Policy Advice, Second Edition Arthur C. Petersen PBL Netherlands Environmental Assessment Agency, Bilthoven

“In this thought-provoking philosophical analysis, Arthur Petersen explores the nature of climate simulation and attendant uncertainties. … His analysis has implications not only for the Intergovernmental Panel on Climate Change and other assessment bodies, but for all who debate the reliability and utility of model simulations as a basis for managing environmental risks in the anthropocene era.”

—Richard Moss, PNNL Joint Global Change Research Institute, University of Maryland

Catalog no. K14379, April 2012, 224 pp.

Soft Cover ISBN: 978-1-4665-0062-4, $59.95 / £38.99 Also available as an eBook

Statistical Geoinformatics for Human Environment Interface Wayne L. Myers and Ganapati P. Patil

Spatial Data Analysis in Ecology and Agriculture Using R Richard E. Plant

The Pennsylvania State University, University Park, USA

University of California, Davis, USA

Illustrating the interdisciplinary nature of geoinformatics, this book presents two paradigms (localization and multiple indicators) for the spatial analysis of human influences and environmental resources. The first approach localizes thematic targets by treating space as a pattern of vicinities, with the pattern being a square grid and the placement of vicinities centrically referenced. The second approach explores human/environment interface as an abstraction through indicators, neutralizing the common conundrum of how to reconcile disparate spatial structures such as points, lines, and polygons.

“… there was a dearth of books mainly catered toward ecologists and agricultural scientists interested in applied exploration of spatially referenced data. Professor Plant fills this void! … the author did a fabulous job in properly sequencing the concept development. … I can certainly say with confidence that this book is expected to enjoy a long shelf life.

If you want to get your hands dirty with some applied spatial data analysis, I highly recommend buying it.”

Catalog no. C2876, July 2012, 223 pp.

ISBN: 978-1-4200-8287-6, $79.95 / £49.99 Also available as an eBook

—Dipankar Bandyopadhyay, Journal of Agricultural, Biological, and Environmental Statistics, October 2012

Catalog no. K11009, March 2012, 648 pp.

ISBN: 978-1-4398-1913-5, $89.95 / £57.99 Also available as an eBook

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

29

Statistics for Engineering and Physical Science Advanced Risk Analysis in Engineering Enterprise Systems

Coming soon!

Time Series with Mixed Spectra

Cesar Ariel Pinto

Ta-Hsin Li IBM Watson Research Center, Yorktown Heights, New York, USA

Parameter estimation of sinusoids in noise still attracts a lot of attention in both statistical and engineering literature because there are seemingly endless alternative solutions to the problem. For the first time, this book provides a comprehensive, systematic, and upto-date survey of important methods developed for parameter estimation of sinusoids in noise. This selfcontained, graduate-level book develops numerous methods and algorithms and then balances their explanations with theoretical analysis. Rather than elaborate on advanced, technical details, the author emphasizes intuition and interpretation behind the theoretical reasoning and results.

Catalog no. C1763, July 2013, 596 pp.

ISBN: 978-1-58488-176-6, $79.95 / £49.99 Also available as an eBook

Old Dominion University, Norfolk, Virginia, USA

Paul R. Garvey The MITRE Corporation, Bedford, Massachusetts, USA

“The book is a decidedly unique and rigorous treatment of selected topics in engineering systems risk analysis and management. The narrative is notably modern and clear. The mathematical formalism is comprehensive and advanced while remaining accessible for those involved in engineering complex systems. … The book will improve the systems engineering community’s ability to address enterprise design risk assessment and management across a system’s lifecycle.”

—James Lambert, University of Virginia

Catalog no. K11256, October 2012, 464 pp.

ISBN: 978-1-4398-2614-0, $99.95 / £63.99 Also available as an eBook

New!

Mark P. Kaminskiy

Essential Statistical Concepts for the Quality Professional

NASA Goddard Space Flight Center, Greenbelt, Maryland, USA

D.H. Stamatis ANHUI University of Finance and Economics, Bengbu, China

Suitable for reliability engineering students and those interested in applied survival data analysis, this up-todate and concise book presents basic reliability concepts and models. The text shows how the models are used in reliability, risk analysis, physics of failure, fracture mechanics, and biological, pharmaceutical, and medical studies. Requiring no special mathematical background, it also introduces a new concept of the Gini-type index.

The essence of any root cause analysis in modern quality thinking is to go beyond the actual problem.

This book offers a new non-technical statistical approach to quality for effective improvement and productivity by focusing on very specific and fundamental methodologies as well as tools for the future.

It examines the fundamentals of statistical understanding; by doing that, the book shows why statistical use is important in the decision-making process.

Catalog no. K16124, November 2012, 152 pp.

ISBN: 978-1-4665-6592-0, $129.95 / £82.00

Catalog no. K14213, May 2012, 510 pp.

ISBN: 978-1-4398-9457-6, $89.95 / £57.99

Reliability Models for Engineers and Scientists

Also available as an eBook

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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 data sets. 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.

• Provides the only integrated account of Bayesian disease mapping • Covers the recently developed INLA package in R • Presents wide-ranging coverage of Bayesian hierarchical regression modeling, including variable selection, missing data, and geographically dependent/adaptive regression • Includes extensive WinBUGS and R resources • Offers data sets and the WinBUGS and R code on the author’s website Catalog no. K14543, April 2013, c. 396 pp.

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

Age-Period-Cohort 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. It compares new and existing models and methods, provides useful guidelines on how to conduct APC analysis, and incorporates examples from sociology, demography, epidemiology, and other disciplines.

• Draws on the authors’ decade-long work on new models, methods, and empirical applications of APC analysis • Includes technical discussions of statistical issues and many empirical applications • Illustrates the use of HAPC models for the aggregate population rates data design in cancer incidence and mortality • Provides software, sample programs, and details on empirical analyses on the book’s web page Catalog no. K14675, February 2013, 352 pp.

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

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