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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

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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3

Introductory Statistics and General References

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

The BUGS BookA PracticalIntroduction toBayesian AnalysisDavid Lunn, Chris Jackson, Nicky Best, Andrew Thomas, andDavid Spiegelhalter

“The most anticipated applied Bayesian text of thelast 20 years, The BUGS Book is like a wonderfulalbum by an established rock supergroup … theauthors have created a masterpiece well worth thewait. The book offers the perfect mix of basic proba-bility calculus, Bayes and MCMC basics, an incredi-bly broad array of useful statistical models, and aBUGS tutorial and user manual complete with all the‘tricks’ one would expect from the team that invent-ed the language. … accessible yet comprehensiveinstruction in its proper use. A must-own for anyworking applied statistical modeler.”

—Bradley P. Carlin, University of Minnesota

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

—Jean-Louis Fouley, CHANCE, 2013

• Covers all the functionalities of BUGS, includingprediction, missing data, model criticism, andprior sensitivity

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

• Includes detailed exercises and solutions on asupporting website

Selected Contents:

Introduction: Probability and Parameters. MonteCarlo Simulations using BUGS. Introduction toBayesian Inference. Introduction to Markov ChainMonte Carlo Methods. Prior Distributions. RegressionModels. Categorical Data. Model Checking andComparison. Issues in Modeling. HierarchicalModels. Specialized Models. DifferentImplementations of BUGS. Appendices. Bibliography.Index.

Catalog no. C8490, October 2012, 399 pp.Soft CoverISBN: 978-1-58488-849-9, $49.95 / £24.99Also available as an eBook

Paradoxes inScientificInferenceMark ChangAMAG Pharmaceuticals, Inc,Lexington, Massachusetts, USA

The paradoxology of scientific inference refers to thestudy of the nature of scientific inference and evidence through controversies or, more precisely,paradoxes. This book analyzes paradoxes from manydifferent perspectives, such as statistics, mathematics,philosophy, science, and artificial intelligence. It compares various quantitative methods of evidencemeasures, 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 infer-ence through studying the paradoxes.

• Presents large collections of paradoxes in the sciences and statistics

• Provides broad and interesting applications ofparadoxes

• Offers a new, effective way of learning scientificinference

• Analyzes controversies in statistical measures ofscientific evidence

• Discusses principles and the conceptual unification of statistical paradigms

• Develops new architectures for creating artificialintelligent agents

• Includes a quick study guide and exercises ineach chapter

Selected Contents:

The Joy of Paradoxes: A Random Walk. Mathematicaland Plausible Reasoning. Statistical Measures ofScientific Evidence. Scientific Principles andInferences. Artificial Intelligence. Appendix.Bibliography. Index.

Catalog no. K14744, October 2012, 291 pp.Soft CoverISBN: 978-1-4665-0986-3, $39.95 / £25.99Also available as an eBook

http://www.crcpress.com/product/isbn/9781584888499


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Introductory Statistics and General References / Statistical Theory and Methods

The R StudentCompanionBrian DennisUniversity of Idaho, Moscow,USA

“An R book for high schoolers! This is an excellentidea, and the quality of the product is equally excellent. It may be suitable for non-calculus-basedintroductory courses at the college level as well. … Dennis does a good job dispelling the ‘steeplearning curve’ myth concerning R … It is high timethat introductory statistics be taught in an engag-ing manner … with meaningful data sets, attractivegraphics, and so on. Dennis’ book is a fine contribu-tion toward that goal.”

—Norman Matloff, Journal of Statistical Software,February 2013

Catalog no. K13498, September 2012, 360 pp.Soft CoverISBN: 978-1-4398-7540-7, $39.95 / £25.99

The A-Z ofError-FreeResearchPhillip I. GoodConsultant, Huntington Beach,California, USA

This practical book begins with an overview ofwhen—and when not—to use statistics. It guidesreaders through the planning and data collectionphases and presents various data analysis techniques.The author then covers techniques for developingmodels that provide a basis for future research. Healso discusses reporting techniques to ensure researchefforts get the proper credit. The book concludes withcase-control and cohort studies. R code is included toimplement the methods.

Catalog no. K14287, August 2012, 269 pp.Soft CoverISBN: 978-1-4398-9737-9, $49.95 / £31.99

R for StatisticsPierre-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 andrelated functions for matrices, arrays, and dataframes is by far the most friendly and helpful intro-duction to the subject that I have seen. … Alldatasets, along with the R code in the book, areavailable on the website for the text. … If you arenot a trained programmer but you aspire to writecode that is efficient and perhaps, from time to time,clever, then this book is a fine place for you to startlearning R.”

—Homer S. White, MAA Reviews, January 2013

Catalog no. K13834, March 2012, 320 pp.Soft CoverISBN: 978-1-4398-8145-3, $59.95 / £34.99Also available as an eBook

Coming soon!

Exercises andSolutions inStatisticalTheoryLawrence L. Kupper,Brian H. Neelon, andSean M. O’BrienDesigned for teaching a statistical theory course in statistics, biostatistics, mathematics, engineering,physics, computer science, psychometrics, and otherdisciplines, this text contains exercises and selectedsolutions in probability theory, univariate distributiontheory, and multivariate distribution theory as well asexercises and selected solutions in estimation theoryand hypothesis testing theory. The exercises vary indifficulty from basic to intermediate to advanced.Solutions for about half the exercises are included,with a separate solutions manual available upon qual-ifying course adoption.

Catalog no. K16626, May 2013, c. 390 pp.Soft CoverISBN: 978-1-4665-7289-8, $59.95 / £38.99Also available as an eBook





5

Statistical Theory and Methods


Coming soon!

Linear Algebraand MatrixAnalysis forStatisticsSudipto BanerjeeUniversity of Minnesota,Minneapolis, USA

Anindya RoyUniversity of Maryland BaltimoreCounty, USA

“This beautifully written text is unlike any other instatistical science. It starts at the level of a firstundergraduate course in linear algebra, and takesthe student all the way up to the graduate level,including Hilbert spaces. It is extremely well craftedand proceeds up through that theory at a very goodpace. The statistics chapters are added at just theright places to motivate the reader and illustrate thetheory. The book is compactly written and mathe-matically rigorous, yet the style is lively as well asengaging. This elegant, sophisticated work will serveupper 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 andmatrix analysis for statistical applications

• Takes a vector-space approach, enabling elegant proofs and smooth transition to morecomplex topics

• Presents recent developments in fields as diverse as spatial statistics, machine learning,and social network analysis

• Requires no prior knowledge of linear algebra

• Includes exercises to enable further understanding of the topics discussed

Selected Contents:

Basic Operations. Systems of Linear Equations. Moreon Linear Equations. Euclidean Spaces. The Rank of aMatrix. Complementary Subspaces. Orthogonality,Orthogonal Subspaces, and Projections. More onOrthogonality. Revisiting Linear Equations.Determinants. Eigenvalues and Eigenvectors.Quadratic Forms. Matrix and Vector Norms. HilbertSpaces. References.

Catalog no. K10023, September 2013, c. 416 pp.ISBN: 978-1-4200-9538-8, $79.95 / £49.99Also available as an eBook

Coming soon!

StatisticalTheoryA ConciseIntroductionFelix AbramovichTel Aviv University, Israel

Ya'acov RitovThe Hebrew University ofJerusalem, Israel

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

The book takes an examples-based approach withclear exposition of key topics and just the rightamount of mathematical formality. It also includesnumerous exercises to enhance the students’ under-standing of the topics discussed.

• Presents a clear and concise introduction to thekey 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:

Introduction. Parameter Estimation. ConfidenceIntervals and Confidence Regions. Large-SampleTheory. Hypotheses Testing. Bayesian Inference.Elementary Decision Theory.

Catalog no. K12383, May 2013, c. 239 pp.ISBN: 978-1-4398-5184-5, $69.95 / £44.99Also available as an eBook





New!

UnderstandingAdvancedStatisticalMethodsPeter WestfallTexas Tech University, Lubbock,USA

Kevin S.S. HenningSam Houston State University,Huntsville, Texas, USA

Designed for students in all disciplines, this text introduces mathematical statistics in intuitive, self-contained, and accessible ways. Simulations andcomputing are used throughout to introduce andillustrate topics. Many exercises and examples spanvarious scientific disciplines. The book discussesBayesian statistics before frequentist statistics, thor-oughly covers populations versus processes, inte-grates design and measurement with analysis, andemphasizes the understanding and use of statisticalmodels as recipes for producing data.

• Provides a unique and accessible scientificallybased introduction to topics of mathematicalstatistics

• Emphasizes simulation and computing withmany data examples

• Presents the necessary concepts in calculus andprobability in a very intuitive way

• Includes numerous exercises, enabling use as acourse text or for self-study

Selected Contents:

Introduction: Probability, Statistics and Science.Random Variables and Their Probability Distributions.Probability Calculation and Simulation. IdentifyingDistributions. Conditional Distributions andIndependence. Marginal Distributions, JointDistributions, Independence, and Bayes’ Theorem.Sampling from Populations and Processes. ExpectedValue and the Law of Large Numbers. Functions ofRandom Variables: Their Distributions and ExpectedValues. Distributions of Totals. Estimation:Unbiasedness, Consistency, and Efficiency. TheLikelihood Function and Maximum LikelihoodEstimates. Bayesian Statistics. Frequentist StatisticalMethods. Are Your Results Explainable by ChanceAlone? Chi-Squared, Student’s t, and F-Distributions,with Applications. Likelihood Ratio Tests. Sample Sizeand Power. Robustness and NonparametricMethods.

Catalog no. K14873, April 2013, c. 567 pp.ISBN: 978-1-4665-1210-8, $79.95 / £44.99Also available as an eBook

Probability and StochasticModelingVladimir I. RotarSan Diego State University,California, USA

“This is a superbly written text on probability andstochastic processes for … upper division students inscience and engineering, including statistics andmathematics, as well as students in fields such aseconomics and finance. … a wonderful book for selfstudy for many others. Important and well-chosenexamples illustrate the theory throughout, and alarge body of exercises supplements the text. … Aspecial feature of this book is a marvelous expositionof many interesting aspects of financial mathemat-ics that are generally considered rather intricate andinaccessible at this level. …”

—Rabi Bhattacharya, University of Arizona

Catalog no. K13311, August 2012, 508 pp.ISBN: 978-1-4398-7206-2, $79.95 / £49.99Also available as an eBook

Coming soon!

StatisticalMethods forHandlingIncompleteDataJae Kwang Kim and Jun ShaoWith advances in computing power, there have beensubstantial developments in computational methodsfor handling missing data. This text presents an intro-duction to the theory, applications, and computation-al aspects of missing data analysis. It covers the threemain methodological approaches: likelihood-based,nonparametric, and quasi-randomization. The textincludes many real examples and integrates comput-er code where appropriate. It also provides exercisesat the end of each chapter.

Catalog no. K12249, August 2013, c. 224 pp.ISBN: 978-1-4398-4963-7, $89.95 / £57.99Also available as an eBook




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FlexibleImputation ofMissing DataStef van BuurenTNO Quality of Life, Leiden, The Netherlands

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

—Andrew Gelman, Columbia University

“… a beautiful book that is so full of guidance forstatisticians … exceptionally up to date and hasmore useful wisdom about dealing with commonmissing data problems than any other source I’veseen.”

—Frank Harrell, Vanderbilt University

Catalog no. K13103, March 2012, 342 pp.ISBN: 978-1-4398-6824-9, $89.95 / £57.99Also available as an eBook

Principles ofUncertaintyJoseph B. KadaneCarnegie Mellon University,Pittsburgh, Pennsylvania, USA

2011 Degroot PrizeWinner

“In this remarkable book, Kadane begins at the mostrudimentary level, develops all the needed mathe-matics on the fly, and still manages to flesh out atleast the core of the whole story, slowly, thoughtful-ly, and rigorously, right up to graduate level. Majortheorems all proved in detail appear here, but notfor their own sake; the author always carefullyselects them … . Highly recommended.”

—D.V. Feldman, CHOICE, February 2012

Catalog no. K12848, May 2011, 503 pp.ISBN: 978-1-4398-6161-5, $89.95 / £59.99Also available as an eBook

MaximumLikelihoodEstimation forSample SurveysRaymond L. Chambers,David G. Steel, Suojin Wang, and Alan WelshThis book presents an overview of likelihood methodsfor the analysis of survey data obtained using methodsthat may result in the sample differing from the pop-ulation. It provides all necessary background materialon likelihood inference and covers a range of datatypes, including multilevel data. Illustrated by numer-ous worked examples using tractable models, it alsoaddresses 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 / £49.99Also available as an eBook

AppliedCategorical andCount DataAnalysisWan Tang, Hua He, and Xin M. TuUniversity of Rochester, New York, USA

This self-contained text explains how to perform thestatistical analysis of discrete data. It covers classic con-cepts and popular topics, such as contingency tables,logistic models, and Poisson regression models. It alsopresents modern areas that include models for zero-modified count outcomes, parametric and semipara-metric longitudinal data analysis, reliability analysis,and methods for dealing with missing values. R, SAS,SPSS, and Stata programming codes are provided forall the examples, enabling readers to immediatelyexperiment with the data in the examples.

Catalog no. K10311, June 2012, 384 pp.ISBN: 978-1-4398-0624-1, $89.95 / £57.99Also available as an eBook







New!

GeneralizedEstimatingEquationsSecond EditionJames W. HardinUniversity of South Carolina,Columbia, USA

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

Praise for the First Edition:

“Generalized Estimating Equations is the first andonly book to date dedicated exclusively to GEEs. …The authors do a good job of not only presentingthe general theory of GEE models, but also givingexplicit examples of various correlation structures,link functions, and a comparison between popula-tion-averaged and subject-specific models. … avaluable reference for researchers, teachers, and stu-dents who study and practice GLIM methodology.”

—Journal of the American Statistics Association, March 2004

This second edition of a bestseller incorporates com-ments and suggestions from a variety of sources,including the Statistics.com course on longitudinaland panel models taught by the authors. Along withdoubling the number of end-of-chapter exercises, thisedition offers more thorough coverage of hypothesistesting and diagnostics, expands discussion of variousmodels associated with GEE, and provides a new pres-entation of model selection procedures. Numerousexamples are employed throughout the text, alongwith the software code used to create, run, and eval-uate the models being examined.

• Provides an overview of the theory and applications of GEEs

• Adopts a practical approach with many examples

• Contains new methods and examples

• 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 EstimatingEquations. Generalized Estimating Equations.Residuals, Diagnostics, and Testing. Programs andDatasets. References. Author Index. Subject Index.

Catalog no. K13819, December 2012, 277 pp.ISBN: 978-1-4398-8113-2, $89.95 / £57.99Also available as an eBook

GeneralizedLinear Modelsand ExtensionsThird EditionJames W. HardinUniversity of South Carolina,Columbia, USA

Joseph M. HilbeCalifornia Institute of Technology,Pasadena, and Arizona StateUniversity, Tempe, USA

This book presents a thorough examination of GLMestimation methods as well as the derivation of allmajor GLM families. Examined families includeGaussian, gamma, inverse Gaussian, binomial,Poisson, geometric, and negative binomial. The textalso contains various models that have been devel-oped on the basis of GLM theory. Using Stata, thebook offers numerous examples to assist readers inapplying the models to their own data situations.

Catalog no. N10590, June 2012, 479 pp.Soft CoverISBN: 978-1-59718-105-1, $79.95 / £49.99

ConfidenceIntervals forProportions and RelatedMeasures ofEffect SizeRobert G. NewcombeCardiff University, Wales

This book illustrates the use of effect size measuresand corresponding confidence intervals as moreinformative alternatives to the most basic and widelyused significance tests. It provides readers with a deepunderstanding of what happens when these statisticalmethods are applied in situations far removed fromthe familiar Gaussian case. Requiring little computa-tional skills, the book offers user-friendly Excel spread-sheets for download at www.crcpress.com, enablingreaders to easily apply the methods to their ownempirical data.





9



GeneralizedLinear MixedModelsModern Concepts,Methods andApplicationsWalter W. StroupUniversity of Nebraska, Lincoln,USA

This text presents an introduction to linear modelingusing the GLMM as an overarching conceptual frame-work. For readers new to linear models, the bookhelps them see the big picture. It shows how linearmodels fit with the rest of the core statistics curricu-lum and points out the major issues that statisticalmodelers must consider.

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

• Emphasizes the connection between studydesign and all aspects of the model

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

• Presents numerous examples using the SAS®

GLIMMIX procedure

• Gives in-depth treatments of issues unique togeneralized and mixed linear modeling, includ-ing conditional versus marginal modeling, broadversus narrow inference space, and data versusmodel-scale inference and reporting

• Offers the data for all exercises as well as SASfiles for all examples at www.crcpress.com

Selected Contents:

PART I The Big Picture: Modeling Basics. DesignMatters. Setting the Stage. PART II Estimation andInference Essentials: Estimation. Inference, Part I:Model Effects. Inference, Part II: CovarianceComponents. 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: RepeatedMeasures. 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 / £57.99Also available as an eBook

Methodology in Robust andNonparametricStatisticsJana Jurecková, Pranab Kumar Sen, and Jan PicekClosely related to nonparametric methods, robust statistical methods are not unduly affected by dataoutliers or other small departures from model assump-tions. This book presents a comprehensive overviewof methodology for robust and nonparametric statis-tics. It covers both methods in parallel to demonstratetheir relative strengths and weaknesses. Using exam-ples to illustrate the methods, the text emphasizesapplications in the fields of biomedical science, bioinformatics, finance, and engineering. Numerousexercises are also included in the text.

Catalog no. K11885, July 2012, 410 pp.ISBN: 978-1-4398-4068-9, $99.95 / £63.99Also available as an eBook

Extreme ValueMethods withApplications toFinanceSerguei Y. NovakMiddlesex University, London, UK

“… there are many new techniques and resultswhich do not exist in other books on extreme valuetheory. … those who want to study in detail the non-parametric methods for heavy-tailed distributionswill find this book a very valuable contribution. … Iwould strongly recommend this book to PhD stu-dents working on extreme value theory [and] tomathematicians, probabilists, and statisticians whowant to know about extreme value theory and non-parametric methods of inference for extremes.”

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







Coming soon!

Analysis ofVariance forFunctional DataJin-Ting ZhangNational University of Singapore

This book presents the updated hypothesis testingmethods developed in the last decade for FDA. Thesubjects covered include reconstructing functionalobservations, Gaussian processes, analysis of variancefor functional data, functional linear models, ill-condi-tioned functional linear models, diagnostics of func-tional observations, variable selection for functionallinear models, Behrens-Fisher problems for functionaldata, test of equal covariance functions, and surfacedata analysis.

Catalog no. K12912, June 2013, c. 333 pp.ISBN: 978-1-4398-6273-5, $99.95 / £63.99Also available as an eBook

Coming soon!

Mean FieldSimulation forMonte CarloIntegrationPierre Del MoralUniversity of Bordeaux, Talence,France

This book deals with both the theoretical foundationsand applications of sequential Monte Carlo methodsand genetic-type particle techniques. These stochasticinteracting particle algorithms belong to the class ofadvanced Monte Carlo methods. The book showshow these powerful computational methods are currently used in computational physics, physicalchemistry, and computational biology for simulatingcomplex systems in high dimensions.

• Provides a pedagogical introduction to the stochastic modeling and theoretical analysis ofinteracting particle algorithms

• Gives a brief, self-contained account of modernmathematical theory useful for analyzing theasymptotic behavior of Feynman-Kac and particle models

• Focuses on finite/countable state-space models

• Presents theoretical probabilistic tools to analyzethe performance of sequential Monte Carlomethods and genetic particle algorithms

Selected Contents:

Sequential Monte Carlo and Genetic ParticleModels: Introduction. Positive Matrices and ParticleRecipes. Some Advanced Particle Recipes.Application Domains: Particle Absorption Models.Markov Chain Analysis. Biology and ChemistryModels. Signal Processing and Bayesian Inference.Interacting Filters. Optimal Control Problems.Markov Chain Monte Carlo Models. InteractingStochastic Algorithms. Financial Mathematics.Stochastic Optimization Algorithms. Rare EventsStochastic Models. Theoretical Aspects: A BriefTreatise on Feynman-Kac Modeling. SemigroupAnalysis. Interacting Particle Algorithms. AdvancedStochastic Analysis Recipes. Unnormalized and PathSpace Particle Measure. Bibliography. Index.

Catalog no. K14505, May 2013, c. 600 pp.ISBN: 978-1-4665-0405-9, $99.95 / £63.99Also available as an eBook

Time SeriesModeling ofNeuroscienceDataTohru OzakiInstitute of StatisticalMathematics, Tokyo, Japan

Due to recent advances in methodology that offer significant improvements over conventional methods,there is increasing interest in the use of time seriesmodels for the study of neuroscience data such asEEG, MEG, fMRI, and NIRS. Accessible to applied statisticians as well as quantitatively trained neurosci-entists, this book includes many real examples thatillustrate the methods and provides useful instructionsfor computational problems, enabling readers todevelop their own computational toolbox to applythe methods to real data.

Catalog no. C4602, January 2012, 574 pp.ISBN: 978-1-4200-9460-2, $99.95 / £63.99Also available as an eBook




11



New!

StatisticalMethods withApplications toDemographyand LifeInsuranceEstáte V. KhmaladzeVictoria University of Wellington,New Zealand

Suitable for statisticians, mathematicians, actuaries,and students interested in the problems of insuranceand analysis of lifetimes, this book presents contemporary statistical techniques for analyzing lifedistributions and life insurance problems. It not onlycontains traditional material but also incorporatesnew problems and techniques not discussed in exist-ing actuarial literature.

• Provides an easy transition from pure mathematics to demography and life insuranceapplications

• Illustrates precise mathematical statementsthrough real-world statistical problems

• Includes new problems and techniques not covered in existing actuarial literature

Selected Contents:

Duration of Life as a Random Variable. Models ofDistribution Functions F(x) and Force of Mortalityµ(x). The Empirical Distribution Function of Durationof Life. Deviation of Fn(x) from F(x) as a RandomProcess. Limit of Empirical Process: Brownian Bridge.Distribution of x2 Goodness-of-Fit Statistic. StatisticalConsequences of What We Have Learned So Far.Testing Parametric Hypotheses. UnexpectedExample—Exponentiality of Durations of Rule ofRoman Emperors. Estimation of the Rate of Mortality.Censored Observations. Related Point Processes.Kaplan-Meier Estimator (Product-Limit Estimator) forF. Statistical Inference about F Based on the Kaplan-Meier 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 ConfidenceBounds for Expected Remaining Life. PopulationDynamics. Bibliography. Index.


New!

Analysis ofMixed DataEdited by

Alexander R. de LeonUniversity of Calgary, Alberta,Canada

Keumhee CarrièreChoughUniversity of Alberta, Edmonton,Canada

This is the first volume to date that provides a unifiedand timely summary of the major advances in the fieldof mixed models. The book traces important develop-ments, collates basic results, presents terminology andmethodologies, and gives an overview of statisticalresearch applications.

• Illustrates modern methods and case studiesusing 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:

Analysis of Mixed Data: An Overview. CombiningUnivariate and Multivariate Random Forests forEnhancing Predictions of Mixed Outcomes. JointTests for Mixed Traits in Genetic Association Studies.Bias in Factor Score Regression and a SimpleSolution. Joint Modeling of Mixed Count andContinuous Longitudinal Data. Factorization andLatent Variable Models for Joint Analysis of Binaryand Continuous Outcomes. Regression Models forAnalyzing Clustered Binary and ContinuousOutcomes under the Assumption of Exchangeability.Random Effects Models for Joint Analysis ofRepeatedly Measured Discrete and ContinuousOutcomes. Hierarchical Modeling of Endpoints ofDifferent Types with Generalized Linear MixedModels. Joint Analysis of Mixed Discrete andContinuous Outcomes via Copula Models. Analysisof Mixed Outcomes in Econometrics: Applications inHealth Economics. Sparse Bayesian Modeling ofMixed Econometric Data Using Data Augmentation.Bayesian Methods for the Analysis of MixedCategorical and Continuous (Incomplete) Data.

Catalog no. K13979, January 2013, 262 pp.ISBN: 978-1-4398-8471-3, $89.95 / £57.99Also available as an eBook





StationaryStochasticProcessesTheory andApplicationsGeorg LindgrenLund University, Sweden

“In many respects, Lindgren’s Stationary StochasticProcesses: Theory and Applications is an updatedand expanded version that has captured much ofthe same spirit (and topics!) as the Cramer andLeadbetter classic. While there have been a numberof new and good books published recently on spatialstatistics, none cover some of the key important top-ics, such as sample path properties and level cross-ings, in a comprehensive and understandable fashion like Lindgren’s book. This book is requiredreading 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 selec-tion of topics within the modern field of stochasticprocesses. … those coming from the theoretical sidewho want to know more about the applications willbenefit from this book. A common theme for thebook is the bridge-building between different audi-ences. … Without being mathematically over-demanding, the book builds up the relevant theoryin a very intuitive yet rigorous way that helps thereader to a deeper understanding of definitions andresults that could otherwise be mystifying. This intu-ition-driven approach also provides a commonthread throughout the book.”

—Claudia Klüppelberg and Morten Grud Rasmussen,Technische Universität München

Selected Contents:

Some Probability and Process Background. SampleFunction Properties. Spectral Representations. LinearFilters: General Properties. Linear Filters: SpecialTopics. Classical Ergodic Theory and Mixing. VectorProcesses and Random Fields. Level Crossings andExcursions.

Catalog no. K15489, October 2012, 375 pp.ISBN: 978-1-4665-5779-6, $89.95 / £57.99Also available as an eBook

Coming soon!

StationaryStochasticProcesses forScientists andEngineersGeorg Lindgren, Holger Lennart Rootzen,and Maria Sandsten

“This book is a lucid and well-paced introduction tostationary stochastic processes, superbly motivatedand illustrated through a wealth of convincingapplications in science and engineering. It offers aclear guide to the formulation and mathematicalproperties of these processes and to some non-sta-tionary processes too, without going too deeply intothe mathematical foundations; the emphasisthroughout is on practical application rather thanmathematical development for its own sake. Thereader will find tools for analysis and calculationand also—importantly—material to deepen under-standing and generate enthusiasm and confidence.An outstanding text.”

—Clive Anderson, University of Sheffield

Based on a course taught to undergraduate studentsin engineering for over 30 years, this text presents allthe material for a first course in stationary stochasticprocesses (SSP). Following naturally from a mathe-matical statistics course, it covers model building viaSSP with a focus on engineering applications. Thebook includes many exercises and computer-basedpracticals using MATLAB®.

• Focuses on engineering topics and applications

• Draws on classroom-tested material

• Presents covariance and Fourier methods,including linear filters in discrete and continuoustime

• Describes statistical estimation techniques, mainly for frequency analysis

• Incorporates exercises and MATLAB-based labsessions

Catalog no. K20279, August 2013, c. 300 pp.ISBN: 978-1-4665-8618-5, $79.95 / £49.99



13

Statistical Theory and Methods / Biostatistics and Epidemiology


StatisticalMethods forStochasticDifferentialEquationsEdited by

Mathieu Kessler,Alexander Lindner, andMichael SorensenThis book presents current research trends and recentdevelopments in statistical methods for stochastic dif-ferential equations. Accessible both to new studentsand seasoned researchers, each self-contained chapterstarts with introductions to the topics and builds grad-ually toward discussing recent research. Written byleading researchers in the field, the book includesapplications to finance and econometrics and provides relevant software where applicable.


Adaptive DesignMethods inClinical TrialsSecond EditionShein-Chung ChowDuke University School ofMedicine, Durham, NorthCarolina, USA

Mark ChangAMAG Pharmaceuticals, Inc,Lexington, Massachusetts, USA

“This second edition remains a useful referencesource for anyone interested in advancing innova-tive trial designs and wishing to incorporate adap-tations, modifications, and changes to the drugdevelopment process. Five new chapters have beenadded and are all worth reading … . For anyoneworking in and studying clinical research, the bookis worth purchasing and will make a valuable addi-tion to any library. … this revision continues to pro-vide a balanced summary of statistical methods,together with the authors’ perspective on currentregulatory practice.”

—International Statistical Review, 80, 2012


Design andAnalysis ofBridgingStudiesEdited by

Jen-pei Liu, Shein-Chung Chow, and Chin-Fu HsiaoTaking into account the International ConferenceHarmonisation E5 framework for bridging studies, thisbook covers the regulatory requirements, scientificand practical issues, and statistical methodology fordesigning and evaluating bridging studies and multi-regional clinical trials. For bridging studies, theauthors explore ethnic sensitivity, the necessity ofbridging studies, types of bridging studies, and theassessment of similarity between regions based onbridging evidence. For multiregional clinical trials, thetext considers regional differences, assesses the consistency of treatment effect across regions, anddiscusses sample size determination for each region.


Design andAnalysis of Non-Inferiority TrialsMark D. Rothmann,Brian L. Wiens, and Ivan S.F. Chan

“… an important resource foranyone involved in designingnon-inferiority trials. The authors weave in manyexamples, primarily in oncology, as well as a largeset of references from the now substantial statisticalliterature on non-inferiority designs. … a must-haveresource … . A portion of a special topics course in abiostatistics department could be built around thisbook, and this exposure would be especially valu-able for students considering a career in or aroundthe pharmaceutical industry.”

—Erica Brittain, Australian & New Zealand Journal ofStatistics, May 2012

Catalog no. C8040, July 2011, 454 pp.ISBN: 978-1-58488-804-8, $93.95 / £59.99Also available as an eBook






Biostatistics and Epidemiology

Coming soon!

BiosimilarsDesign and Analysisof Follow-onBiologicsShein-Chung ChowDuke University School ofMedicine, Durham, NorthCarolina, USA

This is the first book entirely devoted to the designand analysis of biosimilarity assessment and druginterchangeability of biosimilars. It also focuses oncomparability tests in the manufacturing processes ofbiologic products. The book covers all of the statisticalissues that may occur in biosimilar studies under vari-ous study designs at different stages of research anddevelopment of biologic products.

• Represents the first book on biosimilarity ofdrugs and biologic products

• Evaluates various criteria for assessing biosimilarproducts

• Presents the totality biosimilarity index, a general approach for assessing biosimilarity

• Examines study designs for switching or alternating drug interchangeability

Selected Contents:

Introduction. Bioequivalence Experience for DrugProducts. Regulatory Requirement for AssessingFollow-on Biologics. Criteria for Similarity. StatisticalMethods for Assessing Average Biosimilarity. GeneralApproach for Assessing Biosimilarity. Non-Inferiorityversus Equivalence. Assessment of Biosimilarity inVariability. Impact of Variability on Biosimilarity Limitsfor Assessing Follow-on Biologics. DrugInterchangeability. CMC Requirements for BiologicalProducts. Test for Comparability in ManufacturingProcess. Stability Analysis. Current Issues in BiosimilarStudies. References. Index.


Coming soon!

RandomizedPhase II CancerClinical TrialsSin-Ho JungDuke University, Durham, NorthCarolina, USA

Randomized phase II cancer clinical trials are increas-ingly being used in recent years because of lower sample size requirements when multiple treatmentsare being evaluated. This accessible book covers boththe latest developments in methodology as well astraditional single-arm phase II trial methods. It keepsthe statistical level at a minimum so that both statisti-cians and clinicians conducting phase II clinical trialsunderstand the material. The book includes manydiverse statistical designs and analysis methods rele-vant to oncology.

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

• Reviews the statistical methods for single-armphase II trials

• Presents flexible clinical trial designs

Selected Contents:

Introduction. Single-Arm Phase II Trial Designs.Inference on the Binomial Probability in Single-ArmMultistage Clinical Trials. Single-Arm Phase II ClinicalTrials with Time-to-Event Endpoints. Single-ArmPhase II Trials with Heterogeneous PatientPopulations. Randomized Phase II Trials for Selection:No Prospective Control Arms. Randomized Phase IICancer Clinical Trials with a Prospective Control onBinary Endpoints (I): Two-Sample Binomial Test.Randomized Phase II Cancer Clinical Trials with aProspective Control on Binary Endpoints (II): FisherExact Test. Randomized Phase II Trials withHeterogeneous Patient Populations: Stratified Fisher’sExact Test. Randomized Phase II Clinical Trials Basedon Survival Endpoints: Two-Sample Logrank Test.Some Flexible Phase II Clinical Trial Designs.




15



Interval-Censored Time-to-Event DataMethods andApplicationsEdited by

Ding-Geng (Din) Chen,Jianguo Sun, and Karl E. PeaceA practical guide for biomedical researchers, clinicians,biostatisticians, and graduate students in biostatistics,this volume covers the latest developments in theanalysis and modeling of interval-censored time-to-event data. Top researchers from academia, biophar-maceutical industries, and government agencies showhow up-to-date statistical methods are used in realbiopharmaceutical and public health applications.

• Provides up-to-date methodologies for interval-censored time-to-event data

• Offers easy access to computational methodsand R software packages

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

• Formulates statistical analysis plans associatedwith real-world clinical data

Selected Contents:

Introduction and Overview: Overview of RecentDevelopments for Interval-Censored Data. A Reviewof Various Models for Interval-Censored Data.Methodology: Current Status Data in the Twenty-First Century. Regression Analysis for Current StatusData. Statistical Analysis of Dependent Current StatusData. Bayesian Semiparametric Regression Analysis ofInterval-Censored Data with Monotone Splines.Bayesian Inference of Interval-Censored SurvivalData. Targeted Minimum Loss-Based Estimation of aCausal Effect Using Interval-Censored Time-to-EventData. Consistent Variance Estimation in Interval-Censored Data. Applications and RelatedSoftware: Bias Assessment in Progression-FreeSurvival Analysis. Bias and Its Remedy in Interval-Censored Time-to-Event Applications. AdaptiveDecision Making Based on Interval-Censored Data ina Clinical Trial to Optimize Rapid Treatment ofStroke. Practical Issues on Using Weighted LogrankTests. glrt—New R Package for Analyzing Interval-Censored Survival Data. Index.


Joint Models for Longitudinaland Time-to-Event DataWith Applications in RDimitris RizopoulosErasmus University MedicalCenter, Rotterdam, Netherlands

Longitudinal studies often investigate how a markerthat is repeatedly measured in time is associated withan event of interest, such as prostate cancer studieswhere longitudinal PSA level measurements are col-lected in conjunction with the time-to-recurrence.This book provides a full treatment of joint models forlongitudinal and time-to-event data. Emphasizingapplications, the content is explanatory rather thanmathematically rigorous. All illustrations are availablein the R programming language via the author’s freelyavailable JM package.

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

• Introduces various extensions of the standardjoint model, including several parameterizationsfor the association structure and the handling ofcompeting risks

• Covers several diagnostic tools based on residu-als to assess the assumptions behind a jointmodel

• Discusses dynamic predictions for survival andlongitudinal outcomes as well as discriminationconcepts for longitudinal markers

• Emphasizes applications so readers understandthe type of research questions best answeredwith joint models

Selected Contents:

Introduction. Analysis of Longitudinal Data. Analysisof Time-to-Event Data. Joint Models for Longitudinaland Time-to-Event Data. Extensions of the StandardJoint Model. Diagnostics. Survival Probabilities andProspective Accuracy Measures.






Coming soon!

Handbook ofSurvivalAnalysisEdited by

John P. Klein, Joseph G. Ibrahim,Thomas Scheike, andJohannes C. vanHouwelingenThis handbook focuses on the analysis of lifetime dataarising from the biological and medical sciences. Itdeals with semiparametric and nonparametric meth-ods. For investigators new to this field, the book pro-vides an overview of the topic along with examples ofthe methods discussed. It presents both classicalmethods and modern Bayesian approaches to theanalysis of data.

Catalog no. K15384, August 2013, c. 656 pp.ISBN: 978-1-4665-5566-2, $99.95 / £63.99

MultivariateSurvivalAnalysis andCompetingRisksMartin J. CrowderImperial College, University ofLondon, UK

Suitable for graduate students and researchers in sta-tistics and biostatistics as well as those in the medicalfield, epidemiology, and social sciences, this bookintroduces univariate survival analysis and extends itto the multivariate case. It also covers competing risksand counting processes and provides many real-worldexamples, exercises, and R code. The text discussessurvival data, survival distributions, frailty models,parametric methods, multivariate data and distribu-tions, copulas, continuous failure, parametric likelihood inference, and non- and semi-parametricmethods.

Catalog no. K13489, April 2012, 417 pp.ISBN: 978-1-4398-7521-6, $99.95 / £63.99Also available as an eBook

Coming soon!

SurvivalAnalysis inMedicine andGeneticsJialiang LiNational University of Singapore

Shuangge MaYale University, New Haven,Connecticut, USA

This text introduces up-to-date statistical methods forsurvival data analysis in medicine and genetics. Alongwith classical results, it presents new developments ininterval censoring, statistical diagnostics with time-dependent outcomes, analysis of ultrahigh-dimen-sional data sets, cure rate models, and repeated measure data. Suitable for both graduate studentsand biomedical researchers, the text covers applica-tions in cancer studies, medical diagnosis, genetics,and genomics. It provides R code and example datasets online.


DynamicPrediction inClinical SurvivalAnalysisHans van Houwelingenand Hein PutterLeiden University, TheNetherlands

In the last 20 years, dynamic prediction models havebeen extensively used to monitor patient prognosis insurvival analysis. Written by one of the pioneers in thearea, this book synthesizes these developments in aunified framework. It covers a range of models,including prognostic and dynamic prediction of sur-vival using genomic data and time-dependent infor-mation. The text includes numerous examples usingreal data taken from the authors’ collaborativeresearch. R programs are provided for implementingthe methods.

Catalog no. K11593, November 2011, 250 pp.ISBN: 978-1-4398-3533-3, $93.95 / £59.99Also available as an eBook





17



Coming soon!

BayesianMethods inEpidemiologyLyle D. BroemelingBroemeling and Associates,Medical Lake, Washington, USA

A valuable reference for epidemiologists, biostatisti-cians, and graduate students, this book presents anintroduction to epidemiology that uses Bayesian sta-tistical methods to explore the association betweendisease and risk. It includes a brief introduction to theconcepts of epidemiology, the basic elements ofBayesian statistics, and the types of epidemiologicstudies that can be analyzed by Bayesian methods. Foreach problem in epidemiology, the Bayesian analysisis derived and explained.


Handbook ofStatistics inClinicalOncologyThird EditionEdited by

John CrowleyCancer Research and Biostatistics,Seattle, Washington, USA

Antje HoeringCancer Research and Biostatistics, University ofWashington, and Fred Hutchinson Cancer ResearchCenter, Seattle, USA

Addressing the many challenges that have arisen sincethe publication of its predecessor, this third editioncovers the newest developments involved in thedesign and analysis of cancer clinical trials. Accessibleto statisticians in clinical trials as well as oncologistsinterested in clinical trial methodology, this editioncontains numerous figures and examples to betterexplain concepts. New topics in this edition includetrial designs for targeted agents, Bayesian trial design,and the inclusion of high-dimensional data and imag-ing techniques.


Clinical Trials in OncologyThird EditionStephanie Green,Jacqueline Benedetti,Angela Smith, and John CrowleyThe new edition of this bestseller provides a nontech-nical and thoroughly up-to-date review of methodsand issues related to clinical trials. The authors empha-size the importance of proper study design, analysis,and data management and identify the pitfalls inherent in these processes. The book has beenrestructured with separate chapters and expandeddiscussions on general clinical trials issues and issuesspecific to Phases I, II, and III. New sections coverinnovations in Phase I designs, randomized Phase IIdesigns, and overcoming the challenges of array data.


Statistics ofMedicalImagingTianhu LeiPhysical principles and mathematical procedures ofmedical imaging technologies have been extensivelystudied during past decades. However, less work hasbeen done on their statistical aspect. Filling this gap,this book provides a theoretical framework for statisti-cal investigation into medical technologies. Ratherthan offer detailed statistical descriptions of basicimaging protocols of x-ray CT and MRI, the bookpresents a method to conduct similar statistical inves-tigations into more complicated imaging protocols.

Catalog no. C8842, December 2011, 438 pp.ISBN: 978-1-4200-8842-7, $99.95 / £63.99Also available as an eBook









Coming soon!

Statistical andComputationalMethods inBrain ImageAnalysisMoo K. ChungA major challenge in brain mapping is caused by themassive amount of nonstandard high-dimensionaldata that is difficult to analyze using standard techniques. This book covers modern statistical andcomputational techniques for analyzing such data.Methodological topics covered include finite mixturemodels, logistic models, nonparametric regression,mixed effects models, neural networks, and supportvector machines. Real data sets are used to illustratethe methods and MATLAB® code is available online toimplement them.

• Presents a coherent statistical and mathematicaltreatment of methods useful in neuroimagingapplications

• Includes real examples and case studies from top journals

• Emphasizes image visualization using MATLAB

• Offers all of the brain imaging data and codesfrom the text available for download on theauthor’s website

Selected Contents:

Introduction to Brain and Medical Images. BernoulliModels for Binary Images. General Linear Models.Gaussian Kernel Smoothing. Random Fields Theory.Anisotropic Kernel Smoothing. Multivariate GeneralLinear Models. Cortical Surface Analysis. Heat KernelSmoothing on Surfaces. Cosine Series Representationof 3D Curves. Weighted Spherical HarmonicRepresentation. Multivariate Surface Shape Analysis.Laplace-Beltrami Eigenfunctions for Surface Data.Persistence Homology. Sparse Networks. SparseShape Models. Modeling Structural Brain Networks.Mixed Effect Models. Bibliography.

Catalog no. K11644, July 2013, c. 416 pp.ISBN: 978-1-4398-3635-4, $99.95 / £63.99Also available as an eBook

Coming soon!

Applied Meta-Analysis with RDing-Geng ChenUniversity of Rochester, NewYork, USA

Karl E. PeaceJiann-Ping Hsu College of PublicHealth, Georgia SouthernUniversity, 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. Theexamples are based on the actual experiences of theauthors in many areas of clinical drug development.Real examples of clinical trials are presented and afterunderstanding the application, the various clinical trialmethods inherent in the clinical trials are identified.The book’s presentation reflects a case studyapproach.

• Represents one of the first books on meta-analysis with R

• Describes real clinical trials with the associatedclinical data

• Provides a step-by-step approach to using R foranalysis

• Offers data and R code available for downloadonline

Selected Contents:

Introduction to R. Research Protocol for Meta-Analyses. Meta-Analysis for Continuous Data. Meta-Analysis of Categorical Data. Fixed-Effect Meta-Analysis Models. Random-Effect Meta-AnalysisModels. Quantifying Heterogeneity in Meta-Analysis.Meta Regression. Subgroup Analysis. PublicationBiases in Meta-Analysis. Meta-Analysis of aMulticenter Clinical Trial. References. Indices.




19



New!

RegressionModels as aTool in MedicalResearchWerner VachInstitute of Medical Biometry andMedical Informatics, Freiburg,Germany

While regression models have become standard toolsin medical research, understanding how to properlyapply the models and interpret the results is oftenchallenging for beginners. This text presents the fun-damental concepts and important aspects of regres-sion models most commonly used in medicalresearch, including the classical regression model forcontinuous outcomes, the logistic regression modelfor binary outcomes, and the Cox proportional haz-ards model for survival data. The author emphasizesadequate use, correct interpretation of results, appro-priate presentation of results, and avoidance of poten-tial pitfalls.


Applied MedicalStatistics UsingSASGeoff DerUniversity of Glasgow, Scotland,UK

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

“The book would make an excellent reference guidefor medical data analysts with access to base SAS9.3 or a textbook for an introductory and interme-diate graduate biostatistics course. … The thor-oughness of procedures and the consideration theauthors included in the selection of graphs, SAScode, and theory allow this book to be a resourcefulcompanion for medical analysts. If looking for abroad selection of medical analyses using base SAS9.3, this is the book for you … .”

—Journal of Statistical Software, January 2013


New!

BayesianMethods inHealthEconomicsGianluca BaioUniversity College London, UK

Health economics is concerned with the study of thecost-effectiveness of health care interventions. Thisbook provides an overview of Bayesian methods forthe analysis of health economic data. After an intro-duction to the basic economic concepts and methodsof evaluation, it presents Bayesian statistics using min-imal mathematics. It describes cost-effectivenessanalysis from a statistical viewpoint and Bayesian com-putation. Case studies cover cost-effectiveness analy-ses of anti-asthma treatment, influenza vaccinationand cardiovascular treatment. Data sets and WinBUGSand JAGS code are available online.


ComputationalSystems Biologyof CancerEmmanuel Barillot,Laurence Calzone,Philippe Hupe, Jean-Philippe Vert, andAndrei ZinovyevInstitut Curie, Paris, France

“An up-to-date, comprehensive and very readableoverview, this book has plenty for everyone interest-ed in computational systems biology of cancer.Almost all important topics are introduced andexplained, and pointers are given to further work.The bibliography is outstanding. Think of this asyour guide book to the field, as well as a way to getstarted in it.”

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

Melbourne

Catalog no. K11531, August 2012, 461 pp.ISBN: 978-1-4398-3144-1, $79.95 / £49.99






Biostatistics and Epidemiology / Computational Statistics

MedicalBiostatisticsThird EditionAbhaya IndrayanThe third edition of this acclaimed reference focuseson the statistical aspects of medicine with a medicalperspective, showing how biostatistics is a useful toolto manage some medical uncertainties. This editionincludes several new topics, provides expanded cov-erage of many other topics and includes software illus-trations. The author presents step-by-step explana-tions of statistical methods with the help of numerousreal-world examples. Guide charts at the beginning ofthe book enable quick access to the relevant statisticalprocedure.


Coming soon!

Methods ofStatisticalModelEstimationJoseph M. HilbeCalifornia Institute of Technology,Pasadena, and Arizona StateUniversity, Tempe, USA

Andrew P. RobinsonUniversity of Melbourne, Parkville, Australia

In many situations, standard statistical models maynot be suitable for the data being studied; theresearcher will need to construct a model that willprovide appropriate parameter estimates. This bookprovides a step-by-step guide to estimating regressionmodels using optimization, maximum likelihood,quadrature, and simulation. The text allows readers todevelop their own R code for models relevant to thedata they are studying. It begins with backgroundmaterial and basic models, building through to morecomplex situations, such as mixed effects models. Itcontains data from various disciplines, illustrating howthe techniques can be applied to building models forreal data problems.

• Provides a step-by-step guide to model estimation using R

• Covers the four primary methods: optimization,maximum likelihood, quadrature, and simulation

• Includes background on modeling and buildsfrom basic models to more complex setups

• Develops readers’ R skills

• Contains many real data examples to illustratethe methods

Selected Contents:

R as a Modeling Language. Overview of ModelEstimation. Constructing Synthetic Models.Estimation of Gaussian Models. Optimization.Maximum Likelihood Estimation. Estimation UsingQuadrature. Estimation Using Simulation. Selectingthe Optimal Method of Estimation.


Coming soon!

Optimal Designfor NonlinearResponseModelsValerii V. FedorovGlaxoSmithKline, Collegeville,Pennsylvania, USA

Sergei L. LeonovAstraZeneca, Wilmington,Delaware, USA

This book examines the theory of optimal model-based design and provides examples of optimaldesigns for various models, mostly related to biophar-maceutical applications. The authors pay specialattention to adaptive or sequential optimal designs fornonlinear regression models when estimation andoptimal design are performed in stages. The text illus-trates the designs using an application of a first-orderoptimization algorithm in the space of informationmatrices, which is implemented in both MATLAB® andSAS.





21

Computational Statistics


ProgrammingGraphical UserInterfaces in RMichael LawrenceGenentech Research and EarlyDevelopment, South SanFrancisco, California, USA

John VerzaniCUNY/College of Staten Island,New York, USA

Focusing on GUIs within the R language, this bookshows programmers and users how to develop theirown GUIs, enabling them to interface with other lan-guages. The text opens the possibilities of R’s hugeand growing set of statistical methods. The authorscover four different packages for writing GUIs:gWidgets, RGtk2, Qt, and Tcl Tk. Supported by apackage in CRAN that contains all of the code alongwith additional examples, the text is filled withnumerous examples ranging from the very simple todetailed illustrations of how to code actual interfaces.


The R PrimerClaus Thorn EkstrømUniversity of Copenhagen,Frederiksberg, Denmark

“This book provides a good introduction to R, usinga clear layout and detailed, reproducible examples.An ideal tool for any new R user. … A wide range oftopics are covered, making the book suitable for avariety of readers, from undergraduate students toprofessionals new to R. … an extremely helpful intro-duction to a very useful statistical package.”

—Claire Keeble, Journal of Applied Statistics, 2012

Catalog no. K12876, August 2011, 299 pp.Soft CoverISBN: 978-1-4398-6206-3, $39.95 / £26.99Also available as an eBook

StatisticalComputing inC++ and RRandall L. EubankArizona State University, Tempe,USA

Ana KupresaninLawrence Livermore NationalLaboratory, California, USA

This book discusses code development in C++ and R,before going beyond to look at the valuable use ofthese two languages in unison. It covers linear equa-tion solution with regression and linear models moti-vation, optimization with maximum likelihood andnonlinear least squares motivation, and random num-ber generation. While the text does require a workingknowledge of basic concepts in statistics and experi-ence in programming, it does not require knowledgespecific to C++ or R.

Catalog no. C6650, December 2011, 556 pp.ISBN: 978-1-4200-6650-0, $89.95 / £59.99Also available as an eBook

New!

Handbook ofSAS® DATA StepProgrammingArthur LiCity of Hope National MedicalCenter, Los Angeles County,California, USA

This handbook shows readers how best to manageand manipulate data by using the DATA step in SAS,helping them avoid common problems when creat-ing SAS data sets. The author explains that learningsyntax does not solve all problems; rather, a thoroughcomprehension of SAS processing is needed for suc-cessful programming. He also guides readers througha programming task. In most of the examples, theauthor first presents strategies and steps for solvingthe problem, then offers a solution, and finally gives amore detailed explanation of the solution.







Computational Statistics

Data AnalysisUsing StataThird EditionUlrich KohlerSocial Science Research Center,Berlin, Germany

Frauke KreuterUniversity of Maryland, CollegePark, USA

A comprehensive introduction to both statisticalmethods and Stata, this text helps beginners learn thelogic of data analysis and interpretation and easilybecome self-sufficient data analysts. It also offers tipsand tricks for readers already familiar with Stata. Stepby step, the book leads readers through the entireprocess of data analysis, covering the principles ofStata, data manipulation, graphical representation,and programs to automate repetitive tasks. This thirdedition also explores advanced topics such as stan-dard errors in complex survey and multiple imputa-tion.

Catalog no. N10727, August 2012, 497 pp.Soft CoverISBN: 978-1-59718-110-5, $79.95 / £49.99

New!

Introduction to Time SeriesUsing StataSean BeckettiThis work provides a step-by-step guide to essentialtime series techniques, from the incredibly simple tothe quite complex. At the same time, the bookdemonstrates how these techniques can be applied inStata. It emphasizes an understanding of the intuitionunderlying theoretical innovations and an ability toapply them. Real-world examples illustrate the appli-cation of each concept as it is introduced. The authoralso highlights the pitfalls as well as the power of eachnew tool.

Catalog no. N10838, January 2013, 741 pp.Soft CoverISBN: 978-1-59718-132-7, $79.95 / £49.99

A GentleIntroduction to StataRevised Third EditionAlan C. AcockOregon State University,Corvallis, USA

Updated to reflect the new features of Stata 11, thisthird edition continues to help new Stata usersbecome proficient in Stata. This edition includes anew chapter on the analysis of missing data and theuse of multiple-imputation methods. It also providesan extensive revision of the chapter on ANOVA, alongwith additional material on the application of poweranalysis. Each chapter includes exercises and real datasets are used throughout.

Catalog no. N10594, March 2012, 401 pp.Soft CoverISBN: 978-1-59718-109-9, $79.95 / £49.99

A Visual Guideto StataGraphicsThird EditionMichael N. MitchellUCLA Academic TechnologyServices Consulting Group, LosAngeles, California, USA

With over 900 illustrated examples and quick-refer-ence tabs, this edition helps readers quickly create andcustomize high-quality graphs for any type of statisti-cal data. Each graph is displayed in color with simpleand clear instructions that illustrate how to create andcustomize graphs using either Stata commands or theStata Graph Editor. Stata’s powerful graphics systemgives readers complete control over how the elementsof the graph look, from marker symbols to lines, fromlegends to captions and titles, from axis labels to gridlines, and more.

Catalog no. N10565, January 2012, 499 pp.Soft CoverISBN: 978-1-59718-106-8, $89.95 / £57.99





23

Computational Statistics / Statistical Learning and Data Mining


Interpretingand VisualizingRegressionModels UsingStataMichael N. MitchellUCLA Academic TechnologyServices Consulting Group, Los Angeles, California, USA

This book presents a clear treatment of how to care-fully present results from model-fitting in a wide vari-ety of settings. It is indispensable to anyone who hasto present the tangible meaning of a complex modelin a clear fashion, regardless of the audience. Forexample, many experienced researchers start tosquirm when asked to give a simple explanation ofthe applied meaning of interactions in nonlinear mod-els such as logistic regression. The tools in this bookmake this task much more enjoyable and compre-hensible.

Catalog no. N10624, April 2012, 558 pp.Soft CoverISBN: 978-1-59718-107-5, $79.95 / £49.99

New!

Support VectorMachinesOptimization BasedTheory, Algorithms,and ExtensionsNaiyang Deng, Yingjie Tian, andChunhua Zhang

“This book provides a concise overview of SVMs,starting from the basics and connecting to many oftheir most significant extensions. Starting from anoptimization perspective provides a new way of pre-senting the material, including many of the techni-cal details that are hard to find in other texts. Andsince it includes a discussion of many practical issuesimportant for the effective use of SVMs (e.g., featureconstruction), the book is valuable as a reference forresearchers and practitioners alike.”

—Thorsten Joachims, Cornell University


MultilevelandLongitudinalModelingUsing StataVolumes I and II,Third EditionSophia Rabe-HeskethUniversity of California, Berkeley, USA

Anders SkrondalLondon School of Economics, UK

This book examines Stata’s treatment of generalizedlinear mixed models, also known as multilevel or hier-archical models. Volume I covers continuous Gaussianlinear mixed models. Volume II discusses generalizedlinear mixed models for binary, categorical, count,and survival outcomes.

Catalog no. N10560, April 2012, Soft Cover, SetISBN: 978-1-59718-108-2, $149.95 / £95.00

Volume I: Continuous ResponsesCatalog no. N10561, April 2012, Soft Cover, 514 pp.ISBN: 978-1-59718-103-7, $89.95 / £57.99

Volume II: Categorical Responses, Counts, andSurvivalCatalog no. N10563, April 2012, Soft Cover, 484 pp.ISBN: 978-1-59718-104-4, $89.95 / £57.99

EnsembleMethodsFoundations andAlgorithmsZhi-Hua ZhouNanjing University, China

“Professor Zhou’s book is a comprehensive introduc-tion to ensemble methods in machine learning. It reviews the latest research in this exciting area. I learned a lot reading it!”—Thomas G. Dietterich, Oregon State University, ACM

Fellow, and Founding President of the InternationalMachine Learning Society

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

—Fabio Roli, University of Cagliari









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

ClusteringA Data RecoveryApproach, Second EditionBoris MirkinDCS Birkbeck University ofLondon, UK, and NRU HigherSchool of Economics, Moscow,Russia

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


Economic Time SeriesModeling andSeasonalityEdited by

William R. Bell, Scott H. Holan, andTucker S. McElroy

“The list of authors includes some of the leadingcontributors to the literature … All chapters containboth theoretical development and also empiricalapplications to economic series. … an ideal referencefor those interested in recent developments in this lit-erature.”

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

This practical volume covers frequency domain properties of signal extraction filters, the AkaikeInformation Criterion and model selection criteria,diagnostics for seasonal adjustment, calendar adjust-ments of seasonal time series, generalized airline mod-els for modeling seasonality, and much more.


New!

Risk Assessmentand DecisionAnalysis withBayesianNetworksNorman Fenton andMartin NeilQueen Mary University ofLondon, UK

“The book provides sufficient motivation and exam-ples (as well as the mathematics and probabilitywhere needed from scratch) to enable readers tounderstand the core principles and power ofBayesian networks. However, the focus is on ensur-ing that readers can build practical Bayesian net-work models … readers are provided with a toolthat performs the propagation, so they will be ableto build their own models to solve real-world riskassessment problems.”

—Judea Pearl, UCLA Computer Science Departmentand 2011 Turing Award winner

Catalog no. K10450, November 2012, 524 pp.ISBN: 978-1-4398-0910-5, $79.95 / £41.99

QuantitativeOperationalRisk ModelsCatalina Bolancé,Montserrat Guillén, Jim Gustafsson, and Jens Perch NielsenPresenting a nonparametric approach to modelingoperational risk data, this book offers a practical per-spective that combines statistical analysis and man-agement orientations. It covers the statistical theoryprerequisites and summarizes important contributionsmade in the past decade. The authors explain how toimplement the new density estimation methods foranalyzing the loss distribution in operational risk forbanks and insurance companies. They also includeSAS and R routines to implement all of the proceduresdiscussed in the text.

Catalog no. K14258, February 2012, 236 pp.ISBN: 978-1-4398-9592-4, $79.95 / £44.99Also available as an eBook





25

Statistics for Business, Finance, and Economics


StochasticProcesses withApplications toFinanceSecond EditionMasaaki KijimaTokyo Metropolitan University,Japan

Suitable for graduate students and professionals infinancial engineering, operations research, and math-ematical and statistical finance, this updated new edition presents an accessible treatment of the theoryof discrete stochastic processes and their applicationsin finance. By presenting important results in discreteprocesses and showing how to transfer those resultsto their continuous counterparts, the text imparts anintuitive and practical understanding of the subject. Itthoroughly explores applications to the pricing ofderivative securities, corporate bonds, and creditderivatives.


New!

StatisticalMethods forFinancialEngineeringBruno RémillardHEC Montreal, Quebec, Canada

While many financial engineering books are available,the statistical aspects behind the implementation ofstochastic models used in the field are often over-looked or restricted to a few well-known cases. Thisself-contained book guides current and future practi-tioners on implementing the most useful stochasticmodels used in financial engineering. Each chapterintroduces powerful and practical statistical tools nec-essary to implement the models. Throughout the text,examples using MATLAB® illustrate the application ofthe techniques to solve real-world financial problems.MATLAB and R programs are available on the author’swebsite.


New!

RandomDynamicalSystems inFinanceAnatoliy SwishchukUniversity of Calgary, Alberta,Canada

Shafiqul IslamUniversity of Prince EdwardIsland, Charlottetown, Canada

This book provides a variety of RDS for approximatingfinancial models, presents numerous option pricingformulas for these models, and studies the stabilityand optimal control of RDS. Through numerousexamples, the authors explain how the theory of RDScan describe the asymptotic and qualitative behaviorof systems of random and stochastic differential/dif-ference equations in terms of stability, invariant mani-folds, and attractors. They also develop techniques forimplementing RDS as approximations to financialmodels and option pricing formulas.


New!

A Course onStatistics forFinanceStanley L. ScloveUniversity of Illinois, Chicago,USA

This text presents statistical methods for financialinvestment analysis. Providing the connectionbetween elementary statistics courses and quantita-tive finance courses, the book helps both existing andfuture quants improve their data analysis skills andbetter understand the modeling process. It incorpo-rates applied statistics and mathematical statistics andrequires no prior background in finance. The authorintroduces regression analysis, time series analysis,and multivariate analysis step by step using modelsand methods from finance.







Statistics for Business, Finance, and Economics

ComputationalMethods inFinanceAli HirsaCaspian Capital Management,LLC, New York, USA

“A natural polymath, the author is at once ateacher, a trader, a quant, and now an author of abook for the ages. The content reflects the author’svast experience teaching master’s level courses atColumbia and NYU, while simultaneously research-ing and trading on quantitative finance in leadingbanks and hedge funds.”

—Peter Carr, Morgan Stanley and NYU CourantInstitute of Mathematical Sciences

Catalog no. K11454, September 2012, 444 pp.ISBN: 978-1-4398-2957-8, $89.95 / £59.99Also available as an eBook

New!

Getting Startedwith BusinessAnalyticsInsightful Decision-Making David Roi HardoonSAS, Singapore

Galit ShmueliIndian School of Business,Hyderabad

“… a good summary of the analytical solutionsemployed across these industries today, including anupdated vocabulary on new domains such as socialmedia. … Looking back at my career in the field ofbusiness analytics, I realize that it would have beenextremely helpful to have had such a book in hand.It would have provided me with guidance on struc-turing my analytical solutions and would haveinspired me to greater creativity. I hope this bookwill light the spark of curiosity for a new generationof 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

An Introductionto ExoticOption PricingPeter BuchenUniversity of Sydney, Australia

“The book presents an entertaining and captivatingcourse in option pricing, aiming to derive closedform analytical formulas for the prices of exoticoptions in an elegant way, provided such a formulaexists. Thanks to the machinery developed by theauthor and his work group, pricing formulas foreven the most complex exotic options are obtainedfrom elementary pricing formulas using elegantarguments and simple algebraic manipulations, i.e.without lengthy integrations. … a very valuabletreatise on exotic option pricing …”

—Tamás Mátrai, Zentralblatt MATH 1242

Catalog no. C9100, February 2012, 296 pp.ISBN: 978-1-4200-9100-7, $79.95 / £49.99Also available as an eBook

Customer andBusinessAnalyticsApplied Data Miningfor Business DecisionMaking Using RDaniel S. PutlerAlteryx, California, USA

Robert E. KriderSimon Fraser University, Burnaby,British Columbia, Canada

Showing how data mining can improve the perform-ance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities. Itexplains and demonstrates, via the accompanyingopen-source software, how advanced analytical toolscan address various business problems. The authorsalso give insight into some of the challenges facedwhen deploying these tools.

Catalog no. K14501, May 2012, 315 pp.Soft CoverISBN: 978-1-4665-0396-0, $69.95 / £44.99Also available as an eBook





27

Statistics for the Social and Behavioral Sciences


Coming soon!

IncompleteCategoricalData DesignNon-RandomizedResponse Techniquesfor SensitiveQuestions in SurveysGuo-Liang TianThe University of Hong Kong

Man-Lai TangHong Kong Baptist University

This book presents new techniques designed to over-come the bias inherent in posing sensitive questions insociological or behavioral science surveys, withoutrequiring a means of randomization. The authors pro-vide a systematic introduction to NRR techniques thatcan overcome the limitations of RR techniques, com-bining the strengths of existing approaches, such asRR models, incomplete data design, expectation-maximization algorithm, data augmentation algorithm, and the bootstrap method. R codes areprovided for implementing the methods.

Catalog no. K12579, July 2013, c. 230 pp.ISBN: 978-1-4398-5533-1, $89.95 / £57.99Also available as an eBook

A StatisticalGuide for theEthicallyPerplexedLawrence HubertUniversity of Illinois at Urbana-Champaign, USA

Howard WainerNational Board of MedicalExaminers, Pennsylvania, USA

“Using all the resources provided, one can assemblea very long list of issues and applications, with read-ings and references. … recommended … a resourcethe statistically sophisticated teacher can mine formaterial from which to create their own examples toengage students.”

—Robert W. Hayden, MAA Review, December 2012

“A valuable guide for sorting through ethical issuesin 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. K13412, September 2012, 588 pp.Soft CoverISBN: 978-1-4398-7368-7, $49.95 / £31.99Also available as an eBook

Latent MarkovModels forLongitudinalDataFrancesco Bartolucci,Alessio Farcomeni, andFulvia PennoniDrawing on the authors’ extensive research in theanalysis of categorical longitudinal data, this bookfocuses on the formulation of latent Markov modelsand the practical use of these models. It demonstrateshow to use the models in three types of analysis, withnumerous examples illustrating how latent Markovmodels are used in economics, education, sociology,and other fields. The R and MATLAB® routines used forthe examples are available on the authors’ website.

Catalog no. K10884, October 2012, 252 pp.ISBN: 978-1-4398-1708-7, $89.95 / £57.99

Event HistoryAnalysis with RGöran BroströmProfessor Emeritus, UmeåUniversity, Sweden

With an emphasis on social science applications, thisbook presents an introduction to survival and eventhistory analysis. It includes a wide range of real exam-ples, with data available online and supported by adedicated R package for performing all of the analy-ses. Keeping mathematical details to a minimum, theauthor covers both discrete and continuous time data,parametric proportional hazards, and accelerated failure times.







Statistics for the Social and Behavioral Sciences / Environmental Statistics

InformativeHypothesesTheory and Practicefor Behavioral andSocial ScientistsHerbert HoijtinkUniversity Utrecht, TheNetherlands

This detailed book discusses the evaluation of behav-ioral and social science hypotheses that are moreinformative than traditional null and alternativehypotheses. Requiring a minimal prerequisite knowl-edge of multivariate statistics, such as regression andANOVA, it provides relevant information for activeresearchers in the social and behavioral sciences. Thebook considers Bayesian and classical approaches,pays considerable attention to sample size determina-tion, and provides software for all functions discussed.


New!

Data Analysisand Statisticsfor Geography,EnvironmentalScience, andEngineeringMiguel F. AcevedoUniversity of North Texas,Denton, USA

This practical, classroom-tested book helps readerslearn quantitative methodology, including how toimplement advanced analysis methods using anopen-source software platform. The author bringstogether principles of statistics and probability, multi-variate analysis, and spatial analysis methods appliedto a variety of geographical and environmental mod-els. Theory is accompanied by hands-on computerexercises, progressing from easy to difficult. The textalso presents a review of mathematical methods, mak-ing the book self-contained.


Coming soon!

AgriculturalStatistical Data AnalysisUsing StataGeorge BoyhanUniversity of Georgia, Athens,USA

Stata is one of the most widely used statistical analysissoftware packages for investigating experimentaldesign and analysis in agricultural research. Easy toread and user friendly for beginners, this book pro-vides an introduction to Stata and its use in agricul-tural research. It opens with a general discussion ofstatistical software and then covers data entry andapplications of Stata. More advanced topics includethe use of Stata in regression analysis and in analyzingdata that is typically not normally distributed.

Catalog no. K20263, June 2013, c. 264 pp.Soft CoverISBN: 978-1-4665-8585-0, $79.95 / £49.99Also available as an eBook

QuantitativeEcotoxicologySecond EditionMichael C. NewmanCollege of William and Mary,Gloucester Point, Virginia, USA

“Mike Newman’s Quantitative Ecotoxicologyprovides a unique and much-needed addition to theecotoxicological literature. He covers the mostimportant ecotoxicological concepts (bioaccumula-tion, lethal and nonlethal responses to stress at theindividual level, population and metapopulationeffects, and community effects) and effectively com-bines these with the appropriate quantitativeoptions and considerations for assessing theseprocesses. This book is like an ecotoxicology text andstatistics text rolled into one.”

—Valery E. Forbes, University of Nebraska-Lincoln






29

Environmental Statistics


Introduction toHierarchicalBayesianModeling forEcological DataEric ParentENGREF/AgroParisTech, France

Etienne RivotAgrocampus Ouest, INRA,Rennes, France

Making statistical modeling and inference moreaccessible to ecologists and related scientists, thisbook gives readers a flexible and effective frameworkto learn about complex ecological processes from var-ious sources of data. It shows how Bayesian statisticalmodeling provides an intuitive way to organize data,test ideas, investigate competing hypotheses, andassess degrees of confidence of predictions. Data sets,exercises, and R and WinBUGS codes are available onthe authors’ website.

Catalog no. C9195, August 2012, 427 pp.ISBN: 978-1-58488-919-9, $89.95 / £57.99Also available as an eBook

SimulatingNatureA Philosophical Study of Computer-SimulationUncertainties andTheir Role in Climate Science and Policy Advice,Second EditionArthur C. PetersenPBL Netherlands Environmental Assessment Agency, Bilthoven

“In this thought-provoking philosophical analysis,Arthur Petersen explores the nature of climate simu-lation and attendant uncertainties. … His analysishas implications not only for the IntergovernmentalPanel on Climate Change and other assessment bod-ies, but for all who debate the reliability and utilityof model simulations as a basis for managing envi-ronmental risks in the anthropocene era.”

—Richard Moss, PNNL Joint Global Change ResearchInstitute, University of Maryland

Catalog no. K14379, April 2012, 224 pp.Soft CoverISBN: 978-1-4665-0062-4, $59.95 / £38.99Also available as an eBook

StatisticalGeoinformaticsfor HumanEnvironmentInterfaceWayne L. Myers andGanapati P. PatilThe Pennsylvania StateUniversity, University Park, USA

Illustrating the interdisciplinary nature of geoinfor-matics, this book presents two paradigms (localizationand multiple indicators) for the spatial analysis ofhuman influences and environmental resources. Thefirst approach localizes thematic targets by treatingspace as a pattern of vicinities, with the pattern beinga square grid and the placement of vicinities centri-cally referenced. The second approach exploreshuman/environment interface as an abstractionthrough indicators, neutralizing the common conun-drum of how to reconcile disparate spatial structuressuch as points, lines, and polygons.


Spatial DataAnalysis inEcology andAgricultureUsing RRichard E. PlantUniversity of California, Davis,USA

“… there was a dearth of books mainly cateredtoward ecologists and agricultural scientists inter-ested in applied exploration of spatially referenceddata. Professor Plant fills this void! … the author dida fabulous job in properly sequencing the conceptdevelopment. … I can certainly say with confidencethat this book is expected to enjoy a long shelf life.If you want to get your hands dirty with someapplied spatial data analysis, I highly recommendbuying it.”

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







Statistics for Engineering and Physical Science

Coming soon!

Time Serieswith MixedSpectraTa-Hsin LiIBM Watson Research Center,Yorktown Heights, New York,USA

Parameter estimation of sinusoids in noise still attractsa lot of attention in both statistical and engineering literature because there are seemingly endless alterna-tive solutions to the problem. For the first time, thisbook provides a comprehensive, systematic, and up-to-date survey of important methods developed forparameter estimation of sinusoids in noise. This self-contained, graduate-level book develops numerousmethods and algorithms and then balances theirexplanations with theoretical analysis. Rather thanelaborate on advanced, technical details, the authoremphasizes intuition and interpretation behind thetheoretical reasoning and results.


Advanced RiskAnalysis inEngineeringEnterpriseSystemsCesar Ariel PintoOld Dominion University,Norfolk, Virginia, USA

Paul R. GarveyThe MITRE Corporation, Bedford,Massachusetts, USA

“The book is a decidedly unique and rigorous treat-ment of selected topics in engineering systems riskanalysis and management. The narrative is notablymodern and clear. The mathematical formalism iscomprehensive and advanced while remainingaccessible for those involved in engineering complexsystems. … The book will improve the systems engi-neering community’s ability to address enterprisedesign risk assessment and management across asystem’s lifecycle.”

—James Lambert, University of Virginia


New!

ReliabilityModels forEngineers andScientistsMark P. KaminskiyNASA Goddard Space FlightCenter, Greenbelt, Maryland,USA

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


EssentialStatisticalConcepts forthe QualityProfessionalD.H. StamatisANHUI University of Finance and Economics, Bengbu, China

The essence of any root cause analysis in modernquality thinking is to go beyond the actual problem.This book offers a new non-technical statisticalapproach to quality for effective improvement andproductivity by focusing on very specific and funda-mental methodologies as well as tools for the future.It examines the fundamentals of statistical under-standing; by doing that, the book shows why statisti-cal use is important in the decision-making process.






Bayesian Disease MappingHierarchical Modeling in SpatialEpidemiology, Second EditionAndrew B. LawsonMedical University of South Carolina, Charleston, USA

This second edition provides an up-to-date, cohesiveaccount of the full range of Bayesian disease mappingmethods and applications. A biostatistics professor andWHO advisor, the author illustrates the use of Bayesianhierarchical modeling in the geographical analysis of dis-ease through a range of real-world data sets. This editionincludes new chapters on regression and ecologicalanalysis, putative hazard modeling, and disease map sur-veillance as well as new appendices featuring examples ofINLA and CAR models. It also presents expanded materi-al on case event modeling and spatiotemporal analysis.

• Provides the only integrated account of Bayesiandisease mapping

• Covers the recently developed INLA package in R

• Presents wide-ranging coverage of Bayesian hier-archical regression modeling, including variableselection, missing data, and geographicallydependent/adaptive regression

• Includes extensive WinBUGS and R resources

• Offers data sets and the WinBUGS and R code onthe author’s website


Age-Period-Cohort AnalysisNew Models, Methods, and EmpiricalApplicationsYang YangUniversity of North Carolina, Chapel Hill, USA

Kenneth C. LandDuke University, Durham, North Carolina, USA

This book explores the ways in which statisticalmodels, methods, and research designs can be usedto open new possibilities for APC analysis. It com-pares new and existing models and methods, provides useful guidelines on how to conduct APCanalysis, and incorporates examples from sociology,demography, epidemiology, and other disciplines.

• Draws on the authors’ decade-long work onnew models, methods, and empirical applica-tions of APC analysis

• Includes technical discussions of statisticalissues and many empirical applications

• Illustrates the use of HAPC models for theaggregate population rates data design in cancer incidence and mortality

• Provides software, sample programs, anddetails on empirical analyses on the book’sweb page

Catalog no. K14675, February 2013, 352 pp.ISBN: 978-1-4665-0752-4, $79.95 / £49.99Also available as an eBook



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