statistics - october 2010

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Contents

Introductory Probability and Statistics ..............3

Statistical Theory and Methods ........................4

Computational Statistics ................................15

Statistical Learning and Data Mining ..............19

Statistics in Business, Finance, and Economics ..............................................21

Biostatistics ....................................................24

Statistics for Social and Behavioral Sciences..........................................................30

Environmental Statistics ..................................32

Statistics in Genetics, Bioinformatics, andComputational Biology ..................................33

Statistics for Biological Sciences ......................35

Statistics in Engineering and Physical Science ..............................................37

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3

Introductory Probability and Statistics

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

Textbook

Probability and Statisticswith RMaria Dolores Ugarteand Ana F. MilitinoPublic University of Navarre,Pamplona, Spain

Alan ArnholtAppalachian State University,Boone, North Carolina, USA

“… nicely blend[s] mathematical statistics, statisti-cal inference, statistical methods, and computa-tional statistics using S-Plus language... Studentsor self-learners can learn some basic techniques forusing R in statistical analysis on their way to learn-ing about various topics in probability and statis-tics. …”

—Technometrics, May 2009, Vol. 51, No. 2

“… an impressive book … I would recommend itas a useful addition to the bookshelf.”

—Significance, December 2008

Solutions manual available for qualifying instructors

Catalog no. C8911, 2008, 728 pp.ISBN: 978-1-58488-891-8, $89.95 / £51.99

Textbook

An Introductionto StatisticalInference and ItsApplicationswith RMichael W. TrossetIndiana University, Bloomington,USA

With many examples, case studies, and exercises,this text explains how statistical methods are usedfor data analysis and uses the elementary functionsof R to perform the individual steps of statisticalprocedures. It introduces basic concepts of infer-ence through a careful study of several importantprocedures, including parametric and nonpara-metric methods, analysis of variance, and regres-sion. The R code and data sets are available fordownload online.Solutions manual available for qualifying instructors


Textbook

Introduction to Probabilitywith RKenneth P. BaclawskiNortheastern University, Boston,Massachusetts, USA

“… a very interesting book …”—Technometrics, May 2009, Vol. 51, No. 2

“This advanced undergraduate textbook is apleasure to read and this reviewer will definitelyconsider it next time he teaches the subject. … thebook is well usable even if you do not have the timeto include too much programming in your class. Allprograms of the book, and several others, aredownloadable from the book’s website. …”

—MAA Reviews, June 2008

Ancillary materials available for instructors


Textbook

Introduction toProbability andStatistics forScience,Engineering, andFinanceWalter A. RosenkrantzUniversity of Massachusetts,Amherst, USA

“The book provides a very well-written, compre-hensive treatment of all the standard requirementsfor an introductory course … Summing Up: Highlyrecommended.”

—CHOICE, February 2009

This introduction presents many applicationexamples from engineering, computer perform-ance analysis, public health, and finance. It pro-vides technical details for the derivation of varioustheorems, contains over 650 exercises, andincludes a CD-ROM with data sets.Solutions manual available for qualifying instructors






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Statistical Theory and Methods

Handbook of SpatialStatisticsEdited by

Alan E. Gelfand, Peter J. Diggle, Montserrat Fuentes, andPeter Guttorp

Collecting the major work in the field in onesource and including an extensive bibliography,this handbook presents a comprehensive treat-ment of both classical and state-of-the-art aspectsof this maturing area. It takes a unified, integratedapproach to the material, providing cross-refer-ences among chapters.

The book details the evolution of the field andthen focuses on the three main branches of spatialstatistics: continuous spatial variation (point refer-enced data); discrete spatial variation, includinglattice and areal unit data; and spatial point pat-terns. It also contains a section on space–timework as well as a section on important topics thatbuild upon earlier chapters.

Features

• Provides broad thorough coverage of thisvibrant area, from historical to contemporarytopics

• Focuses on continuous and discrete spatial vari-ation, spatial point patterns, and spatio-tempo-ral processes

• Presents the theory and applications with real-world data examples

• Explores the modeling advances, computation-al approaches, and new methodology thathave emerged in recent years

• Covers multivariate spatial process models, spa-tial aggregation, spatial misalignment, and spa-tial gradients in depth

• Draws on contributions from highly regardedinternational experts

Catalog no. C7287, March 2010, 619 pp.ISBN: 978-1-4200-7287-7, $99.95 / £63.99

Coming soon!

Handbook of Markov ChainMonte CarloMethods and ApplicationsEdited by

Steve Brooks, Andrew Gelman, Galin Jones,and Xiao-Li Meng

This comprehensive handbook brings togethermajor advances that have occurred in recent yearswhile incorporating enough introductory materialfor new users of MCMC. It covers theoretical foun-dations, algorithmic and computational method-ology, and realistic case studies from a variety ofdisciplines.

The case studies demonstrate the application ofMCMC methods and serve as a series of templatesfor the construction, implementation, and choiceof MCMC methodology.

Catalog no. C7941, March 2011, c. 800 pp.ISBN: 978-1-4200-7941-8, $99.95 / £63.99

LongitudinalData AnalysisEdited by

Garrett Fitzmaurice,Marie Davidian, Geert Verbeke, and Geert Molenberghs

“…I find this book very useful for statisticians andresearchers in many fields … . Many of the chap-ters include examples and case studies in differentdisciplines and some of this material can be foundon the website of this book. … This handbook willhave, without any doubt, an important place onthe shelf of those statisticians and appliedresearchers working with longitudinal data.”—Journal of Applied Statistics, Vol. 36, No. 10, October

2009

Includes datasets software programs and other material for download





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Introduction toTime SeriesModelingGenshiro KitagawaInstitute of StatisticalMathematics, Tokyo, Japan

With a focus on the description, modeling, predic-tion, and signal extraction of times series, thisbook provides basic tools for analyzing time seriesthat arise in real-world problems. It encouragesreaders to build models for their own real-lifeproblems.

The author employs the state-space model as ageneric tool for time series modeling and presentsconvenient recursive filtering and smoothingmethods, including the Kalman filter, the non-Gaussian filter, and the sequential Monte Carlo fil-ter, for the state-space models.

He takes a unified approach to model evaluationbased on the entropy maximization principleadvocated by Dr. Akaike. He also covers standardstationary time series models, nonstationary timeseries models, and simulation methods.

Features

• Presents a model-based method of analyzing,predicting, and simulating time series with vari-ous characteristics

• Uses real data sets from economics, finance,seismology, meteorology, and ship engineering

• Extends the state-space approach to more gen-eral nonlinear or non-Gaussian state-spacemodels

• Includes methods and models developed bythe author and his colleagues at the Institute ofStatistical Mathematics

Catalog no. C9217, April 2010, 296 pp.ISBN: 978-1-58488-921-2, $79.95 / £49.99

New!Textbook

Time SeriesModeling,Computation, andInferenceRaquel PradoUniversity of California, SantaCruz, USA

Mike WestDuke University, Durham, North Carolina, USA

Focusing on Bayesian approaches and computa-tions using up-to-date simulation-based methodsfor inference, this text integrates mainstreamapproaches for time series modeling with signifi-cant recent developments in methodology andapplications of time series analysis. It encompassesa graduate-level account of Bayesian time seriesmodeling and analysis, a broad range of refer-ences to state-of-the-art approaches to univariateand multivariate time series analysis, and emerg-ing topics at research frontiers.

Features

• Covers the major areas of modern time seriesmodels and theory, including time and spectraldomain and univariate and multivariate timeseries methods

• Includes a wealth of examples implementedusing R

• Presents analyses of real time series data innumerous examples and case studies to illus-trate the flexibility and practical impact of themodels and methods

• Emphasizes model-based, computationallyintensive analysis of structured time series

• Discusses recent techniques for modeling timeseries data, such as dynamic graphical models,SMC methods, and nonlinear/non-Gaussiandynamic models

• Includes a collection of end-of-chapter exercises

• Offers many of the data sets, R and MATLABcode, and other material on the authors’ web-sites

Catalog no. C9336, May 2010, 368 pp.ISBN: 978-1-4200-9336-0, $89.95 / £57.99





New!

StatisticalInferenceAn IntegratedBayesian/LikelihoodApproachMurray AitkinUniversity of Melbourne,Australia

Filling a gap in current Bayesian theory, this bookpresents a unified Bayesian treatment of parame-ter inference and model comparisons that can beused with simple diffuse prior specifications. Thisnovel approach provides new solutions to difficultmodel comparison problems and offers directBayesian counterparts of frequentist t-tests andother standard statistical methods for hypothesistesting.

Emphasizing the principles of Bayesian inferenceand Bayesian model comparison, this book devel-ops a unique methodology for solving challenginginference problems. It gives alternatives to currentfrequentist nonparametric methods and includesnew goodness-of-fit methods for assessing para-metric models.

Features

• Provides new, straightforward solutions forcomparing statistical models

• Offers a unified approach to all model compar-ison problems that avoids difficulties of Bayesfactors and p-values by employing the full pos-terior distribution of the likelihood

• Explains how improper, diffuse, and noninfor-mative priors are used for both parameterinference and model comparison

• Presents a general alternative to the design-based approach for finite population inferenceusing a simple multinomial model and Dirichletpriors

• Discusses how to identify the best model viathe stochastic ordering of deviance distribu-tions

Catalog no. C3436, June 2010, 254 pp.ISBN: 978-1-4200-9343-8, $89.95 / £57.99

New!

Applied BayesianHierarchicalMethodsPeter D. CongdonUniversity of London, UK

Through illustrative data analysis and attention tostatistical computing, this work focuses on thepractical implementation of Bayesian hierarchicalmethods. It also discusses several issues that arisewhen applying Bayesian techniques in hierarchicaland random effects models.

The book provides examples of the followingapplication settings: meta-analysis, data structuredin space or time, multilevel and longitudinal data,multivariate data, nonlinear regression, and sur-vival time data. For the worked examples, the textmainly employs the WinBUGS package. It alsoincorporates BayesX code, which is particularlyuseful in nonlinear regression. To demonstrateMCMC sampling from first principles, the authorincludes worked examples using the R package.

Features

• Presents an up-to-date review of Bayesian hier-archical methods, emphasizing applicationsand practical computing aspects

• Provides a complete treatment of the mainmodeling settings, including meta-analysis,time series, nonlinear regression, and multi-level, multivariate, panel, spatial, and survivaldata

• Illustrates MCMC sampling from first principlesusing R

• Includes realistic worked examples from thesocial and health sciences, along with the codein WinBUGS and BayesX

• Offers a set of programs linked to the workedexamples on www.crcpress.com




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New!Textbook

Bayesian Ideasand DataAnalysisAn Introduction forScientists andStatisticiansRonald Christensen,Wesley Johnson, Adam Branscum, and Timothy E. Hanson

Emphasizing the use of WinBUGS and R to analyzereal data, the text presents statistical tools toaddress scientific questions. It highlights founda-tional issues in statistics, the importance of makingaccurate predictions, and the need for scientistsand statisticians to collaborate in analyzing data.The WinBUGS code provided offers a convenientplatform to model and analyze a wide range ofdata.

The first five chapters of the book contain corematerial that spans basic Bayesian ideas, calcula-tions, and inference. The text also covers MonteCarlo methods, linear structures in regression,binomial regression, normal regression, analysis ofvariance, and Poisson regression. It then extendssome of these methods to handle correlated data.The authors also focus on survival analysis, binarydiagnostic testing, and nonparametric inference.

Features

• Covers a large number of statistical models

• Emphasizes the elicitation of reasonable priorinformation

• Explores numerical approximations via simula-tion

• Uses WinBUGS and R for computational prob-lems

• Reviews basic concepts of matrix algebra andprobability

• Includes numerous exercises and real-worldexamples throughout

• Provides data, programming code, and othermaterials at www.stat.unm.edu/~fletcher

Catalog no. K10199, July 2010, 516 pp.ISBN: 978-1-4398-0354-7, $69.95 / £44.99

Textbook

BayesianMethods forData AnalysisThird EditionBradley P. CarlinUniversity of Minnesota,Minneapolis, USA

Thomas A. LouisJohns Hopkins Bloomberg Schoolof Public Health, Maryland, USA

“…I am glad to see that the software code andexamples have also been made available on thewebsite … a very worthy edition and I highly rec-ommend it as a textbook, and for people who dealwith biostatistics problems regularly as a goodintroduction into the literature. Libraries whichhave the second edition are encouraged to buy thisedition as well.”—Journal of Applied Statistics, Vol. 37, No. 4, April 2010



New!

Bayesian ModelSelection andStatisticalModelingTomohiro AndoKeio University, Kanagawa,Japan

Along with many practical applications, this bookpresents an array of Bayesian inference and modelselection procedures. It thoroughly explains theconcepts, illustrates the derivations of variousBayesian model selection criteria through exam-ples, and provides R code for implementation. TheR code is available for download on the book’swebsite. The text also applies Bayesian modelaveraging to many problems and compares thedifferent types of simulation-based Bayesianmodel selection criteria.

Catalog no. K11633, May 2010, 300 pp.ISBN: 978-1-4398-3614-9, $89.95 / £63.99






New!Textbook

Design ofExperimentsAn IntroductionBased on LinearModelsMax MorrisIowa State University, Ames, USA

Offering deep insight into the connectionsbetween design choice and the resulting statisticalanalysis, this text explores how experiments aredesigned using the language of linear statisticalmodels. It presents an organized framework forunderstanding the statistical aspects of experi-mental design as a whole within the structure pro-vided by general linear models, rather than as acollection of seemingly unrelated solutions tounique problems.

The text enables readers to fully appreciate thefundamental concepts and techniques of experi-mental design as well as the real-world value ofdesign. It gives them a profound understanding ofhow design selection affects the informationobtained in an experiment.

Features

• Discusses the explicit relationship betweenexperimental design and the quality of dataanalysis

• Presents the fundamental concepts and tech-niques of experimental design

• Describes specific forms or classes of experi-mental designs

• Contains an introduction to design for regres-sion models

• Performs calculations using R, with commandsprovided in an appendix

• Incorporates actual experiments drawn fromthe scientific and technical literature

• Includes many end-of-chapter exercises Solutions manual available for qualifying instructors

Catalog no. C9233, July 2010, 370 pp.ISBN: 978-1-58488-923-6, $89.95 / £39.99

New!Textbook

Design andAnalysis ofExperimentswith SASJohn LawsonBrigham Young University, Provo,Utah, USA

This textbook provides practical guidance on thecomputer analysis of experimental data. It con-nects the objectives of research to the type ofexperimental design required, describes the actu-al process of creating the design and collecting thedata, shows how to perform the proper analysis ofthe data, and illustrates the interpretation ofresults.

The book covers both classical ideas in experi-mental design and the latest research topics. Itclearly discusses the objectives of a research proj-ect that lead to an appropriate design choice, thepractical aspects of creating a design and per-forming experiments, and the interpretation ofthe results of computer data analysis.

Features

• Emphasizes the connection between the exper-imental units, the way treatments are random-ized to experimental units, and the propererror term for an analysis of data

• Uses SAS 9.2 throughout to illustrate the con-struction of experimental designs and analysisof data

• Shows how to display experimental resultsgraphically using SAS 9.2 ODS graphics

• Provides uniform coverage on experimentaldesigns and design concepts that are mostcommonly used in practice

• Presents many applications from the pharma-ceutical, agricultural, industrial chemicals, andmachinery industries

• Offers all the SAS code for examples athttp://lawson.mooo.com





9



Textbook

Design andAnalysis ofExperimentsClassical andRegressionApproaches with SASLeonard C. OnyiahSt. Cloud State University,Minnesota, USA

Using both manual methods and SAS programs tocarry out analyses, this modern, comprehensivetext presents classical and regression approachesto experimental design and analysis. The authorprovides examples to illustrate numerous designs,includes the full SAS code and outputs, and offerend-of-chapter exercises to encourage hands-onSAS programming experience.Solutions manual available for qualifying instructors


Textbook

StochasticProcessesAn Introduction,Second EditionPeter W. Jones and Peter SmithKeele University, Staffordshire,UK

Using Mathematica® and R, this updated text dis-cusses the modeling and analysis of randomexperiments using the theory of probability. Itillustrates discrete random processes through theclassical gambler’s ruin problem and its variants,covers continuous random processes, and pro-vides many worked examples and problems. Thebook’s website includes the Mathematica and Rprograms.Solutions manual available for qualifying instructorsvia password on the book’s website

Catalog no. K10004, January 2010, 232 pp.Soft Cover, ISBN: 978-1-4200-9960-7$79.95 / £34.99

Analysis of Messy DataVolume 1DesignedExperiments, Second EditionGeorge A. Milliken andDallas E. JohnsonKansas State University,Manhattan, USA

“…Every chapter has been systematically rewrittenfor greater clarity, and added explanatory materi-al has been inserted throughout. Many new dia-grams and redrawn diagrams have been provided;those that show how to lay out the experimentaldesigns are just superb and extraordinarily clear.The reference list has increased … . This revision ishighly recommended to those who plan and ana-lyze experiments of the type described.”

—International Statistical Review (2009), 77, 2


Visualizing Data Patternswith MicromapsDaniel B. CarrGeorge Mason University,Fairfax, Virginia, USA

Linda Williams PickleStatNet Consulting, LLC,Gaithersburg, Maryland, USA

“The book is extremely well written. … It is obviousthat the authors are in total command of the topicand bring years of experience in the field to theproject. … The reader gains a good understandingof what [micromaps] are for and what they canand cannot accomplish.”—Oliver Schabenberger, SAS Institute Inc., Cary, North

Carolina, USA

“This is a terrific book and it introduces some clevertools.”

—David Berrigan, NIH/NCI








Hidden MarkovModels for TimeSeriesAn IntroductionUsing RWalter ZucchiniUniversity of Gottingen,Germany

Iain L. MacDonaldUniversity of Cape Town, SouthAfrica

This book presents an accessible overview ofHMMs for analyzing time series data, from contin-uous-valued, circular, and multivariate series tobinary data, bounded and unbounded counts,and categorical observations. It also discusses howto employ the freely available computing environ-ment R to carry out computations for parameterestimation, model selection and checking, decod-ing, and forecasting. All of the data sets analyzedin the text are provided online.


New!

Expansions andAsymptotics forStatisticsChristopher G. SmallUniversity of Waterloo, Ontario,Canada

Providing a broad toolkit of analytical methods,this book shows how asymptotics, when coupledwith numerical methods, becomes a powerful wayto acquire a deeper understanding of the tech-niques used in probability and statistics. Itdescribes core ideas in statistical asymptotics; cov-ers Laplace approximation, the saddle-pointmethod, and summation of series; and supple-ments some topics with relevant Maple™ com-mands.


New!

SimultaneousInference inRegressionWei LiuUniversity of Southampton, UK

With examples and MATLAB® programs, this bookprovides a thorough overview of the constructionmethods and applications of simultaneous confi-dence bands for various inferential purposes. Mostof the text covers normal-error linear regressionmodels, although the author also describes thelogistic regression model to show how simultane-ous confidence bands can be constructed andused for generalized linear regression models.MATLAB programs, along with color figures, areavailable for download on the author’s website.

Catalog no. K11385, October 2010, 292 pp.ISBN: 978-1-4398-2809-0, $89.95 / £57.99

New!

Circular and LinearRegressionFitting Circles andLines by LeastSquaresNikolai ChernovUniversity of Alabama atBirmingham, USA

This book explains how to use modern algorithmsto fit geometric contours to observed data inimage processing and computer vision. It looks athow the numerical algorithms relate to one anoth-er through underlying ideas, compares thestrengths and weaknesses of each algorithm, andillustrates how to combine the algorithms toachieve the best performance. MATLAB® codes areavailable on the author’s website.

Catalog no. K11619, June 2010, 286 pp.ISBN: 978-1-4398-3590-6, $99.95 / £63.99





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New!Textbook

NonparametricStatisticalInferenceFifth EditionJean Dickinson Gibbonsand SubhabrataChakrabortiUniversity of Alabama,Tuscaloosa, USA

Covering the most commonly used nonparamet-ric procedures, this bestselling book carefullystates the assumptions, develops the theorybehind the procedures, and illustrates the tech-niques using realistic research examples from thesocial, behavioral, and life sciences. The fifth edi-tion thoroughly revises at least 50 percent of thematerial. The text also contains many tables need-ed for finding P values and obtaining confidenceinterval estimates of parameters.


Mixed EffectsModels forComplex DataLang WuUniversity of British Columbia,Vancouver, Canada

Presenting effective approaches to address missingdata, measurement errors, censoring, and outliersin longitudinal data, this work covers linear, non-linear, generalized linear, nonparametric, andsemiparametric mixed effects models. It discussescomputational strategies for likelihood estimationsof mixed effects models, briefly describes general-ized estimating equations methods and Bayesianmixed effects models, and includes real-worlddata examples from studies on mental distress,AIDS, and more.

Catalog no. C7402, January 2010, 431 pp.ISBN: 978-1-4200-7402-4, $89.95 / £57.99

New!

Robust NonparametricStatistical MethodsSecond EditionThomas P. HettmanspergerPennsylvania State University, University Park, USA

Joseph W. McKeanWestern Michigan University, Kalamazoo, USA

With an emphasis on Wilcoxon rank methods thatenable a unified approach to data analysis, thisbook presents a unique overview of robust non-parametric statistical methods. Drawing on exam-ples from various disciplines, the relevant R codefor these examples, as well as numerous exercisesfor self-study, the text covers location models,regression models, designed experiments, andmultivariate methods. This edition features a newchapter on cluster correlated data.

Catalog no. K10449, December 2010c. 552 pp., ISBN: 978-1-4398-0908-2$99.95 / £63.99

New!

Handbook ofFitting StatisticalDistributionswith RZaven A. KarianDenison University, Granville,Ohio, USA

Edward J. DudewiczSyracuse University, New York,USA

Along with in-depth coverage of cutting-edge,real-world applications and contributions fromexperts who offer deep insight on a range of top-ics, this comprehensive and authoritative hand-book presents the latest and best methods, algo-rithms, and computations for fitting distributionsto data. The book covers GLD methodology, fit-ting systems, and recent additions to GLD andgeneralized bootstrap methods. The accompany-ing CD-ROM includes the R programs used formany of the computations.

Catalog no. C7117, October 2010, 1718 pp.ISBN: 978-1-58488-711-9, $149.95 / £95.00







New!Textbook

Introduction toGeneral andGeneralizedLinear ModelsHenrik Madsen and Poul ThyregodTechnical University of Denmark,Lyngby

Providing a flexible framework for data analysisand model building, this text focuses on the sta-tistical methods and models that can help predictthe expected value of an outcome, dependent, orresponse variable. It offers a sound introduction togeneral and generalized linear models using thepopular and powerful likelihood techniques.Numerous examples show how the problems aresolved with R. Ancillaries are available on thebook’s website.

Catalog no. C9155, October 2010, 318 pp.ISBN: 978-1-4200-9155-7, $79.95 / £39.99

Linear ModelMethodologyAndre I. KhuriProfessor Emeritus, University ofFlorida, Gainesville, USA

Supported by a large number of examples, thisbook provides a strong foundation in the theory oflinear models and explores the latest develop-ments in data analysis. It encompasses a wide vari-ety of topics in linear models that incorporate theclassical approach and more recent trends andmodeling techniques. The author emphasizes thecentral role matrices have played in the moderndevelopment of linear models.


Textbook

An Introductionto GeneralizedLinear ModelsThird EditionAnnette J. DobsonUniversity of Queensland,Herston, Australia

Adrian G. BarnettQueensland University ofTechnology, Kelvin Grove, Australia

“…explanations are fundamentally sound … . Thisis a very worthwhile book: a good class text and apractical reference for applied statisticians.”

—Biometrics

“… This book is an excellent resource, either as anintroduction to or a reminder of the technicalaspects of generalized linear models and providesa wealth of simple yet useful examples and datasets.”

—Journal of Biopharmaceutical Statistics, Issue 2

Catalog no. C9500, 2008, 320 pp., Soft CoverISBN: 978-1-58488-950-2, $60.95 / £39.99

New!

Choice-BasedConjoint AnalysisModels and DesignsDamaraju Raghavarao,James B. Wiley, andPallavi ChitturiTemple University, Philadelphia,Pennsylvania, USA

Building on the authors’ significant work in thefield, this book explores the experimental designissues that occur when constructing concept pro-files for DCE and CA studies. It show how to mod-ify commonly used designs and models as well asdevelop new types of designs for solving DCE andCA problems. The text explains experimentaldesign concepts through illustrative examples andprovides detailed coding of design matrices forstandard designs.

Catalog no. K10020, August 2010, 192 pp.ISBN: 978-1-4200-9996-6, $89.95 / £57.99





13



Textbook

A Primer on Linear ModelsJohn F. MonahanNorth Carolina State University,Raleigh, USA

“…I like the idea of avoiding leaps in the develop-ment and proofs, or referring to other sources forthe details of the proofs. This is a useful, well-writ-ten, instructive book.”

—International Statistical Review, 2008

“…would serve well as the textbook for an intro-ductory course in linear models, or as a referencefor researchers who would like to review the theoryof linear models.”

—Justine Shults, University of Pennsylvania School ofMedicine, Journal of Biopharmaceutical Statistics, 2009

Includes exercises of varying difficulty at the end ofeach chapter


RegressionModelingMethods, Theory,and Computationwith SASMichael PanikUniversity of Hartford,Connecticut, USA

“In his book, Michael Panik takes up many aspectsof modeling with a pedagogical approach, helpingthe reader to understand the process of the prob-lem and proposed methods. … this book is a verygood tool for students and teachers in statistics,but also for researchers wishing to improve theirknowledge in statistical modeling to apply it intheir expertise domain.”

—Christian Derquenne, Journal of Statistical Software,February 2010


Textbook

AppliedStatisticalInference withMINITAB®Sally A. LesikCentral Connecticut StateUniversity, New Britain, USA

Through clear, step-by-step mathematical calcula-tions, this text provides a solid understanding ofhow to apply statistical techniques usingMINITAB®. It focuses on the concepts of confi-dence intervals, hypothesis testing, validatingmodel assumptions, and power analysis. Data setsand a trial version of MINITAB are included onaccompanying CD-ROMs.Solutions manual available for qualifying instructors


Textbook

LogisticRegressionModelsJoseph M. HilbeJet Propulsion Laboratory,California Institute ofTechnology, Pasadena, andArizona State University, Tempe,USA

This text presents an overview of the full range oflogistic models, including binary, proportional,ordered, and categorical response regression pro-cedures. It illustrates how to apply the models tomedical, health, environmental/ecological, physi-cal, and social science data. Stata is used to devel-op, evaluate, and display most models while Rcode is given at the end of most chapters.Example data sets are accessible online in variousformats.Solutions manual available for qualifying instructors








ROC Curves for ContinuousDataWojtek J. KrzanowskiUniversity of Exeter, UK

David J. HandImperial College, London, UK

This book brings together all the relevant materialto impart a clear understanding of how to analyzeROC curves. It provides illustrative examples of themajor methodological developments and surveysthe uses made of the methodology across a rangeof different areas. It also lists a number of websitesfrom which software implementing the varioustechniques can be downloaded.

Catalog no. K10031, 2009, 232 pp.ISBN: 978-1-4398-0021-8, $69.95 / £42.99

StatisticalSimulationPower MethodPolynomials andOtherTransformationsTodd C. HeadrickSouthern Illinois University,Carbondale, USA

Focusing on both univariate and multivariate non-normal data generation, this book presents tech-niques for conducting a Monte Carlo simulationstudy. It shows how to use power method poly-nomials for simulating univariate and multivariatenonnormal distributions with specified cumulantsand correlation matrices. The author employsMathematica® in a range of procedures and offersthe source code for download online.


AntedependenceModels forLongitudinalDataDale L. ZimmermanUniversity of Iowa, Iowa City,USA

Vicente A. Núñez-AntónThe University of the BasqueCountry (UPV/EHU), Bilbao,Spain

“…This book is the first one dedicated entirely toantedependece models … Several relevant R func-tions are available for download from the firstauthor’s webpage … applied researchers will bevery satisfied with the availability of R functions tofit antedependence models to their data. … a wel-come addition to the bibliography of longitudinaldata, combining rigorous statistical presentationwith interesting real-life examples.”

—Raúl E. Macchiavelli, SORT, Vol. 34 (1), 2010


New!

TestingStatisticalHypotheses ofEquivalence andNoninferioritySecond EditionStefan WellekCentral Institute of MentalHealth, Mannheim, and University of Heidelberg,Germany

Giving much more attention to noninferiority test-ing, this second edition provides a rich repertoireof efficient solutions to specific equivalence andnoninferiority testing problems frequentlyencountered in the analysis of real data sets. It alsoincludes new chapters on equivalence tests formultivariate data and tests for relevant differencesbetween treatments. Updated computer pro-grams in SAS, Fortran, and R for facilitating theroutine application of testing procedures are avail-able online at www.crcpress.com






15

Computational Statistics


SAS and RData Management,Statistical Analysis,and GraphicsKen KleinmanHarvard Medical School, Boston,Massachusetts, USA

Nicholas J. HortonSmith College, Northampton,Massachusetts, USA

An all-in-one resource for using SAS and R to carryout common tasks, this book provides a pathbetween languages that is easier than readingcomplete documentation. Through the extensiveindexing, cross-referencing, and worked examplesin the text, users can directly find and implementthe material they need.

The book enables easier mobility between the twosystems: SAS users can look up tasks in the SASindex and then find the associated R code while Rusers can benefit from the R index in a similarmanner. Demonstrating the code in action andfacilitating exploration, the authors present exten-sive example analyses that employ a single dataset from the HELP study.

Features

• Presents a broad set of data management,analysis, and graphical tasks in SAS and R

• Provides parallel examples in SAS and R todemonstrate how to use the software andderive identical answers regardless of softwarechoice

• Gives insight into the process of statistical cod-ing from beginning to end by supplyingworked examples of complex coding tasks

• Contains gentle introductions to complexissues and stumbling blocks new usersencounter

• Covers the ODS and new graphics of SAS 9.2

• Includes an index for each software, allowingusers to easily locate procedures

• Offers the SAS and R data sets and code online


New!

Using R for DataManagement,StatisticalAnalysis, andGraphicsNicholas J. HortonSmith College, Northampton,Massachusetts, USA

Ken KleinmanHarvard Medical School, Boston, Massachusetts, USA

Helping to improve analytical skills, the book lucid-ly summarizes the aspects of R most often used bystatistical analysts. New users of R will find the sim-ple approach easy to understand while moresophisticated users will appreciate the invaluablesource of task-oriented information. The textincludes convenient indices organized by topicand R syntax and contains many example analy-ses. Data sets and code are available for downloadon the book’s website.

Catalog no. K11360, July 2010, 297 pp.Soft Cover, ISBN: 978-1-4398-2755-0$59.95 / £38.99

New!

Using SAS forDataManagement,StatisticalAnalysis, andGraphicsKen KleinmanHarvard Medical School, Boston,Massachusetts, USA

Nicholas J. HortonSmith College, Northampton, Massachusetts, USA

This book presents an easy way to learn how toperform an analytical task in SAS. It covers datamanagement, descriptive summaries, inferentialprocedures, regression analysis, multivariate meth-ods, and the creation of graphics. The textincludes convenient indices organized by topicand SAS syntax and contains many exampleanalyses. Data sets and code are available fordownload on the book’s website.

Catalog no. K11361, July 2010, 305 pp.Soft Cover, ISBN: 978-1-4398-2757-4$59.95 / £38.99






Textbook

Graphics forStatistics andData Analysiswith RKevin J. KeenUniversity Northern BritishColumbia, Prince George,Canada

This text presents the basic principles of soundgraphical design and applies these principles toengaging examples using the graphical functionsavailable in R. The author emphasizes the funda-mentals of statistical graphics and describes thestrengths and weaknesses of each graphical dis-play. The book includes examples of real-worlddata, end-of-chapter exercises, and many illustra-tions, with some in color. R code is available fordownload on the book’s website.


A Handbook ofStatisticalAnalyses Using RSecond EditionBrian S. EverittKing’s College, University ofLondon, UK

Torsten HothornLudwig-Maximilians-UniversitätMünchen, Germany

Like its bestselling predecessor, this second editionprovides a guide to data analysis using the R sys-tem for statistical computing. This edition containsnew chapters on graphical displays, generalizedadditive models, and simultaneous inference aswell as a new section on generalized linear mixedmodels. The authors include new examples andmore exercises in several chapters, along with anew version of the HSAUR package.

Catalog no. C7933, January 2010, 376 pp.Soft Cover, ISBN: 978-1-4200-7933-3$54.95 / £34.99

New!

MultipleComparisonsUsing RFrank BretzNovartis Pharma AG, Basel,Switzerland

Torsten HothornLudwig-Maximilians-UniversitätMünchen, Germany

Peter WestfallTexas Tech University, Lubbock, USA

Adopting a unifying theme based on maximumstatistics, this self-contained introduction describesthe common underlying theory of multiple com-parison procedures through numerous examples.It covers a range of multiple comparison proce-dures and presents a detailed description of avail-able software implementations in R. The R pack-ages and source code for the analyses are availableat http://CRAN.R-project.org


A Handbook ofStatisticalAnalyses usingSASThird EditionGeoff DerUniversity of Glasgow, Scotland

Brian S. EverittKing's College, University ofLondon, UK

… Like the first two editions, this edition empha-sizes how to conduct a range of statistical analysesusing SAS 9.2. … The SAS programs and data areavailable online. … the new graphic proceduresand ODS graphics can be used for presenting theresults. I expect that SAS users will appreciate thisfeature of the edition. … SAS users will find the newedition quite useful.

—Technometrics, November 2009, Vol. 51, No. 4






17



New!

Exploratory MultivariateAnalysis by Example Using RFrancois Husson, Sebastien Le, and Jerome PagesAGROCAMPUS OUEST, Rennes, France

This book covers principal components analysis,correspondence analysis, mixed models, and mul-tiple factor analysis. Examples lead the discussionof the methods and many graphics emphasizevisualization.

Taking a practical approach, the authors keepmathematical content to a minimum or, whennecessary, relegate it to the appendices. The textincludes real-world examples drawn from a rangeof scientific disciplines and implemented using anR package developed by the authors.

Catalog no. K11614, November 2010c. 240 pp., ISBN: 978-1-4398-3580-7$79.95 / £49.99

Introduction toScientificProgrammingand SimulationUsing ROwen Jones, Robert Maillardet, andAndrew RobinsonUniversity of Melbourne,Parkville, Australia

“The authors have written an excellent introduc-tion to scientific programming with R. Their clearprose, logical structure, well-documented code andrealistic examples made the book a pleasure toread. … I would strongly recommend this book forreaders interested in using R for simulations, par-ticularly for those new to scientific programming orR. … would be suitable either as a course textbookor for self-study.”

—Significance, September 2009


Textbook

ComputationalStatisticsAn Introduction to RGünther SawitzkiStatLab, Heidelberg, Germany

“… a well-written and nicely organized book suit-able for quantitatively and computationallysophisticated readers. … it is the integration ofinteresting examples and associated R code thatmake the text a pleasure to read and workthrough. The examples are neither overly trivial …nor excessively complicated, and the R code is sim-ilarly accessible without being either too simple orcomplex. …”

—Ronald D. Fricker, Jr., The American Statistician

Ancillary materials, selected solutions and code avail-able online


Textbook

InteractiveGraphics forData AnalysisPrinciples andExamplesMartin TheusMunich, Germany

Simon UrbanekMadison, New Jersey, USA

“…Interactive Graphics for Data Analysis gives youthe ideas and tools to visualise, explore and under-stand all your data. … [It] also introducesMondrian, a powerful, easy-to-use tool that allowsyou to generate and explore everything shown. …A brief, powerful book with excellent and cleargraphics. … You have no excuse not to use it.”

—Times Higher Education, December 2009

Ancillary materials, including slides and course suggestions available online








An Introductionto StataProgrammingChristopher F. BaumBoston College, Chestnut Hill,Massachusetts, USA

This work focuses on three types of Stata pro-gramming: do-file programming, ado-file pro-gramming, and Mata functions that work in con-junction with do- and ado-files. It explains how tousefully automate work with Stata and how to useStata more effectively through programming onone or more of these levels. “Cookbook” chapterslook at how to perform a specific programmingtask with Stata and provide a complete solution tothe problem.

Catalog no. N10106, 2009, 362 pp.Soft Cover, ISBN: 978-1-59718-045-0$69.95 / £44.99

New!

DataManagementUsing StataA PracticalHandbookMichael N. MitchellUCLA Academic TechnologyServices Consulting Group, LosAngeles, California, USA

This book comprehensively covers data manage-ment tasks that bridge the gap between raw dataand statistical analysis. The author takes a modularapproach that enables readers to quickly identifyand implement the necessary task without havingto access background information first. Each sec-tion in the chapters presents a self-contained les-son that illustrates a particular data managementtask via examples. The text also discusses how toavoid common pitfalls.

Catalog no. N10304, May 2010, 406 pp.Soft Cover, ISBN: 978-1-59718-076-4$69.95 / £44.99

New!

A GentleIntroduction toStataThird EditionAlan C. AcockOregon State University,Corvallis, USA

Updated to reflect the new features of Stata 11,this third edition continues to help new Stata usersbecome proficient in Stata. This edition includes anew chapter on the analysis of missing data andthe use of multiple-imputation methods. It alsoprovides an extensive revision of the chapter onANOVA, along with additional material on theapplication of power analysis.

Catalog no. N10321, August 2010, 393 pp.Soft Cover, ISBN: 978-1-59718-075-7$79.95 / £49.99

New!

MaximumLikelihoodEstimation withStataFourth EditionWilliam Gould, Jeffrey Pitblado, andBrian PoiStataCorp LP, College Station, Texas, USA

This edition explains how to compute maximumlikelihood estimators that are not available asprepackaged routines. It introduces the theory ofmaximum likelihood estimation with particularattention on the practical implications for appliedwork. It then describes the four types of likelihoodevaluator programs. The text also includes detailsabout the ml command, provides checklists to fol-low when writing evaluators, and shows how towrite estimation commands.

Catalog no. N10332, November 2010c. 352 pp., Soft CoverISBN: 978-1-59718-078-8, $79.95 / £49.99





19

Statistical Learning and Data Mining


New!

BayesianArtificialIntelligenceSecond EditionKevin B. Korb and Ann E. NicholsonMonash University, Clayton,Victoria, Australia

Updated and expanded, the second edition of thisbestseller provides a practical and accessible intro-duction to the main concepts, foundation, andapplications of Bayesian networks. This editioncontains a new chapter on Bayesian network clas-sifiers, along with new applications and case stud-ies. It also includes new sections on object-orient-ed Bayesian networks, causal discovery, Markovblanket discovery, and causal discovery programs.Supplemental materials are available on the book’swebsite.


New!

Statistical Data MiningUsing SASApplicationsSecond EditionGeorge FernandezUniversity of Nevada, Reno, USA

This resource describes statistical data mining con-cepts and methods and includes 13 user-friendlySAS macro applications for performing completedata mining tasks. Along with many new featuresin the SAS-specific macro applications, this secondedition now provides access to SAS macros direct-ly from your desktop and offers the ability to cre-ate publication quality graphics. Compiled datamining SAS macro files are available for downloadonline.


New!

Exploratory DataAnalysis withMATLAB®Second EditionWendy L. MartinezThe Department of Defense,Fredericksburg, Virginia, USA

Angel R. MartinezJeffrey L. Solka

Praise for the First Edition

“… The audience for the book is a wide one andincludes statisticians, computer scientists, and oth-ers who may be interested in or use EDA. … I foundthe book to be engagingly written, and successfulin its defined task of teaching the reader to use EDAwith MATLAB. I liked the graphics and thoughtthat they fully illustrated the techniques used.”—Brian Jersky, Sonoma State University, Journal of the

American Statistical Association

New edition includes state-of-the-art techniquesand algorithm descriptions and an upgraded tool-box in each chapter.


New!

Data Miningwith RLearning with CaseStudiesLuis TorgoUniversity of Porto, Portugal

“If you want to learn how to analyze your datawith a free software package that has been built byexpert statisticians and data miners, this is yourbook. A broad range of real-world case studieshighlights the breadth and depth of the R soft-ware.”

—Bernhard Pfahringer, University of Waikato, NewZealand

This hands-on book uses practical examples toillustrate the power of R and data mining. A sup-porting website provides data sets and R code.







Statistical Learning and Data Mining

Temporal Data MiningTheophano MitsaSoftware Consultant, Melrose,Massachusetts, USA

“… the text is highly accessible irrespective of thereader’s prior familiarity with the subject. An exten-sive bibliography is provided on each of the topicscovered, which makes this book a valuable refer-ence for both the novice and the established prac-titioner. The clear, concise and instructive style willmake this book particularly attractive to graduatestudents, researchers, and industry professionals.”

—Wasim Q. Malik, MIT and Harvard Medical School,Cambridge, USA


New!

Handbook ofEducational DataMiningEdited by

Cristobal Romero andSebastian VenturaUniversity of Cordoba, Spain

Mykola PechenizkiyEindhoven University of Technology, The Netherlands

Ryan BakerWorcester Polytechnic Institute, Massachusetts, USA

Reflecting the multidisciplinary nature of the EDMcommunity, this handbook provides a thoroughoverview of the current state of knowledge in thisfield. The first part of the book includes nine sur-veys and tutorials on the principal data miningtechniques that have been applied in education.The second part presents a set of 25 case studiesthat give a rich overview of the problems thatEDM has addressed.


New!

Relational DataClusteringModels, Algorithms,and ApplicationsBo LongYahoo! Labs, Sunnyvale,California, USA

Zhongfei ZhangState University of New York,Binghamton, USA

Philip S. YuUniversity of Illinois at Chicago, USA

This book provides a complete, self-containedintroduction to advances in relational data cluster-ing. It presents a novel theoretical framework aswell as the most state-of-the-art models for rela-tional data clustering. The authors also describe afamily of new algorithms for various relational clus-tering problems arising in a wide range of impor-tant applications. Concepts and theory areexplained through detailed application examples.


Handbook ofNaturalLanguageProcessingSecond EditionEdited by

Nitin IndurkhyaUniversity of New South Wales,Sydney, Australia

Fred J. DamerauGoshen, Connecticut, USA

“… If you need a readable introduction to thisimportant subject — this is it. … This is a goodway to get into NLP. … Highly recommended.”

—Mike James, iProgrammer, 2010

This edition offers greater prominence to statisticalapproaches, a new applications section, a broadermultilingual scope to include Asian and Europeanlanguages, and an actively maintained wiki thatprovides online resources, supplementary infor-mation, and up-to-date developments.

Catalog no. C5921, February 2010, 704 pp.ISBN: 978-1-4200-8592-1, $99.95 / £63.99





21

Statistics in Business, Finance, and Economics


Monte CarloMethods andModels inFinance andInsuranceRalf KornUniversity of Kaiserslautern,Germany

Elke KornIndependent Consultant,Stelzenberg, Germany

Gerald KroisandtFraunhofer ITWM, Kaiserslautern, Germany

Offering a unique balance between applicationsand calculations, this book incorporates the appli-cation background of finance and insurance withthe theory and applications of Monte Carlo meth-ods. It presents recent methods and algorithms,including the multilevel Monte Carlo method, thestatistical Romberg method, and the Heath–Platenestimator, as well as recent financial and actuarialmodels, such as the Cheyette and dynamic mor-tality models.

Through its many numerical and graphical illustra-tions and simple, insightful examples, this bookprovides a deep understanding of the scope ofMonte Carlo methods and their use in variousfinancial situations. The intuitive presentationencourages readers to implement and furtherdevelop the simulation methods.

Features

• Provides detailed descriptions of financial andactuarial models and Monte Carlo simulationalgorithms

• Enables readers to find the right algorithm fora desired application

• Illustrates complicated methods and algorithmswith simple applications to provide an easyunderstanding of key properties

• Describes recent financial models and MonteCarlo simulation methods

Catalog no. C7618, February 2010, 484 pp.ISBN: 978-1-4200-7618-9, $89.95 / £57.99

Textbook

StochasticFinancial ModelsDouglas KennedyTrinity College, Cambridge, UK

“This book is a superb beginning level text for sen-ior undergraduate/graduate mathematicians,which is based on lectures delivered by its author tomany generations of appreciative Cambridgemathematicians. … this readable book will makeits material available to a worldwide audience. …the book contains 40 pages of fully worked outsolutions … .”

—M.A.H. Dempster, Centre for Financial Research,Statistical Laboratory, University of Cambridge, UK


Coming soon!Textbook

StochasticFinanceA NumeraireApproachJan VecerColumbia University, New York,New York, USA

Based on quantitative finance courses taught atColumbia University, this text presents a novelapproach to pricing derivatives contracts usingnumeraire techniques. Focusing on fundamentalfinance principles instead of mathematical theory,the author considers the price of an asset as anexchange ratio between goods that pay for eachother. This approach leads to simple derivations ofpricing formulas that are model independent. Thetext includes illustrative examples, end-of-chapterexercises, and key solutions.

Catalog no. K10632, January 2011, c. 340 pp.ISBN: 978-1-4398-1250-1, $69.95 / £44.99






New!

Introduction toCredit RiskModelingSecond EditionChristian BluhmMunich, Germany

Ludger OverbeckUniversity of Giessen, Germany

Christoph WagnerMunich, Germany

This second edition contains a new section onmulti-period models and discusses recent devel-opments in structured credit. Along with manyworked out examples and numerical results, thisedition also includes an expanded section on tech-niques for the generation of loss distributions aswell as discussions of new topics, such as spectralrisk measures, an axiomatic approach to capitalallocation, and nonhomogeneous Markov chains.

Catalog no. C8992, June 2010, 384 pp.ISBN: 978-1-58488-992-2, $79.95 / £49.99

New!

Handbook ofSolvency forActuaries andRisk ManagersTheory and PracticeArne SandstromSwedish Insurance Federation,Stockholm, Sweden

A one-stop shop for actuaries and risk managers,this handbook presents a complete overview ofsolvency and the European Solvency II standardformula. It discusses the development of solvencyand risk management as well as the modeling andcalibration of the specific standard formula devel-oped for Solvency II. The book also covers themodeling of capital charges in a general settingand highlights key concepts in enterprise risk man-agement.


Textbook

Applied Statisticsfor Business andEconomicsRobert M. LeekleyIllinois Wesleyan University,Bloomington, USA

After reading this book, students will be able tosummarize data in insightful ways using charts,graphs, and summary statistics as well as makeinferences from samples, especially about relation-ships. Numerous interesting and important exam-ples reflect real-life situations and calculations canbe performed using any standard spreadsheetpackage. To help with the examples, the authoroffers both actual and hypothetical databases onhis website.Solutions manual available for qualifying instructors

Catalog no. K10296, March 2010, 496 pp.ISBN: 978-1-4398-0568-8, $79.95 / £49.99

New!

Operational Risk ModellingandManagementClaudio FranzettiSERV, Zurich, Switzerland

Helping you navigate the tricky world of risk cal-culation and management, this book presents twomain building blocks for determining how muchcapital needs to be reserved for operational risk.While R scripts are used for some examples, a pro-totypical software program for calculating the lossdistribution and economic capital in the moredetailed run-through example can be down-loaded from www.garrulus.com






23



New!

Handbook of EmpiricalEconomics and FinanceEdited by

Aman UllahUniversity of California, Riverside, USA

David E. A. GilesUniversity of Victoria, British Columbia, Canada

Handbook of Empirical Economics and Financeprovides an up-to-date reference source of cut-ting-edge developments in applied econometricsand the modeling of special types of economicand financial data. Leading researchers in the fieldcontribute state-of-the-art, previously unpublishedchapters that address these developments.

The handbook covers major themes in the areas ofmicroeconometrics, macroeconometrics, financialeconometrics, panel and spatial data, time-seriesanalysis, semiparametric and nonparametricmethods, and treatment effects. It also discussescomputation with reference to Bayesian methodsas well as information-theoretic approaches toinference.

Features

• Presents contributions from leading interna-tional researchers in all areas of econometrics

• Deals with recent major developments in theapplication of econometric methods to alltypes of data

• Highlights the interface between econometricmethods and financial models

• Provides a balanced viewpoint of differentphilosophical positions and statistical tools

Contents

Microeconometrics. Panel Data and SpatialEffects. Time-Series Analysis. Nonparametric andSemiparametric Methods. Financial Econometrics.Treatment Effects. Macroeconometrics.Computation, Bayesian, and InformationTheoretic Methods.

Catalog no. C7035, December 2010c. 522 pp., ISBN: 978-1-4200-7035-4$149.95 / £95.00

Introduction toSpatialEconometricsJames LeSageMcCoy College of BusinessAdministration, San Marcos,Texas, USA

R. Kelley PaceLouisiana State University, BatonRouge, USA

“…With the empirical illustrations and MATLABtoolbox provided online, the book … is a valuablereference for students and researchers who areinterested in theoretical specifications and empiri-cal applications of spatial models. …”

—Lung-Fei Lee and Jihai Yu, Geographical Analysis 42(2010)

“… a landmark in raising the bar in the field ofapplied spatial econometrics. …”—Spatial Economic Analysis, Vol. 5, No. 1, March 2010


Micro-econometricsUsing StataRevised EditionA. Colin CameronUniversity of California,California, USA

Pravin K. TrivediIndiana University, Bloomington,Indiana, USA

Updated to reflect Stata 11, this revised editionoffers a complete and up-to-date survey of micro-econometric methods available in Stata. Theauthors employ the new margins command,emphasizing both marginal effects at the meansand average marginal effects. They also replacethe xi command with factor variables and presentthe new gmm command for generalized methodof moments and nonlinear instrumental-variablesestimation.

Catalog no. N10276, March 2010, 750 pp.Soft Cover, ISBN: 978-1-59718-073-3$89.95 / £57.99





Biostatistics

New!

Monte CarloSimulation forthePharmaceuticalIndustryConcepts,Algorithms, and CaseStudiesMark ChangAMAG Pharmaceuticals, Lexington, Massachusetts, USA

Helping you become a skillful “simulator,” thisbook provides broad coverage of the entire drugdevelopment process, from drug discovery to pre-clinical and clinical trial aspects to commercializa-tion. It presents the theories and methods neededto carry out computer simulations efficiently, cov-ers both descriptive and pseudocode algorithmsthat provide the basis for implementation of thesimulation methods, and illustrates real-worldproblems through case studies.

The book offers a systematic treatment of com-puter simulation in drug development. It not onlydeals with the principles and methods of MonteCarlo simulation, but also the applications in drugdevelopment, such as statistical trial monitoring,prescription drug marketing, and molecular dock-ing.

Features

• Encompasses various types of simulations indrug development at the micro, macro, andmeta scales

• Discusses virtual data sampling, game theory,deterministic and stochastic decision theories,adaptive trial design methods, Petri nets,genetic programming, and resampling meth-ods

• Presents the necessary algorithms for imple-menting the simulations and sample JavaScriptcoding

• Provides computer source code at www.statisti-cians.org

• Includes many case studies, practical examples,and end-of-chapter exercises

Catalog no. K11621, September 2010, 564 pp.ISBN: 978-1-4398-3592-0, $89.95 / £57.99

New!

Frailty Models in SurvivalAnalysisAndreas WienkeMartin-Luther-University Halle-Wittenberg, Germany

Accessible to nonspecialists, this book explains thebasic ideas in frailty modeling and statistical tech-niques, with a focus on real-world data applicationand interpretation of the results. By applying sev-eral models to the same data, it allows for thecomparison of their advantages and limitationsunder varying model assumptions. The book alsoemploys simulations to analyze the finite samplesize performance of the models.

The text extensively explores how univariate frailtymodels can represent unobserved heterogeneity.It also emphasizes correlated frailty models asextensions of univariate and shared frailty models.The author analyzes similarities and differencesbetween frailty and copula models, discussesproblems related to frailty models, and describesparametric and semiparametric models using bothfrequentist and Bayesian approaches.

Features

• Covers univariate and correlated frailty modelsin detail

• Introduces the concept of heterogeneity in sur-vival analysis

• Compares different extensions of univariatefrailty models to multivariate models

• Illustrates problems with examples based onseveral real data sets

• Includes applications from medicine, epidemi-ology, genetic epidemiology, and demography

• Shows how to implement the models in R,SAS, and Stata

• Offers an extensive list of references that high-light state-of-the-art research




25

Biostatistics


New!

Clinical TrialMethodologyKarl E. Peace and Ding-Geng (Din) ChenJiann-Ping Hsu College of PublicHealth, Georgia SouthernUniversity, Statesboro, USA

From ethical issues and sample size considerationsto adaptive design procedures and statisticalanalysis, this book covers the methodology thatspans every clinical trial regardless of the area ofapplication. Drawing from the authors’ courses onthe subject as well as the first author’s more than30 years working in the pharmaceutical industry, italso discusses bioequivalence clinical trials andincorporates real-world case studies of clinical tri-als from the authors’ own experiences.


New!

Clinical Trial Data Analysisusing RDing-Geng (Din) Chen and Karl E. PeaceJiann-Ping Hsu College of Public Health, Georgia SouthernUniversity, Statesboro, USA

With real-world examples of clinical drug develop-ment, this book provides a thorough presentationof clinical trial methodology. Case studies demon-strate how to select the appropriate clinical trialdata. The authors introduce the correspondingbiostatistical analysis methods, followed by thestep-by-step data analysis using R. They also offerR programs for download, along with other essen-tial data, on their website.


Design andAnalysis ofClinical Trialswith Time-to-Event EndpointsEdited by

Karl E. PeaceJiann-Ping Hsu College of PublicHealth, Georgia SouthernUniversity, Statesboro, USA

This comprehensive resource provides a thoroughpresentation of the design, monitoring, analysis,and interpretation of clinical trials in which time-to-event is of critical interest. Drawing on theexpert contributors’ experiences working in bio-medical research and clinical drug development, itcovers an array of time-to-event methods andexplores an assortment of real-world applications,including analgesic, antibiotic, antiviral, cancerand cardiovascular prevention and optimal assign-ment of treatments.


New!

An Introductionto SurvivalAnalysis UsingStataThird EditionMario ClevesUniversity of Arkansas forMedical Sciences, Little Rock,USA

William Gould, Roberto Gutierrez, and Yulia MarchenkoStataCorp LP, College Station, Texas, USA

This work provides the foundation to understandvarious approaches for analyzing time-to-eventdata. This updated third edition highlights newfeatures of Stata 11, including competing-risksanalysis and the treatment of missing values viamultiple imputation. Other additions include newdiagnostic measures after Cox regression, Stata’snew treatment of categorical variables and inter-actions, and a new syntax for obtaining predictionand diagnostics after Cox regression.

Catalog no. N10331, November 2010c. 412 pp., Soft CoverISBN: 978-1-59718-074-0, $79.95 / £49.99






Biostatistics

New!Textbook

Exercises andSolutions inBiostatisticalTheoryLawrence L. Kupper andBrian H. NeelonUniversity of North Carolina,Chapel Hill, USA

Sean M. O’BrienDuke Clinical Research Institute, Durham, North Carolina,US

Exercises and Solutions in Biostatistical Theorypresents an unusual collection of problems andsolutions that illustrate theoretical concepts essen-tial to understanding the underlying principles ofthe field of biostatistics. Each chapter begins witha review of basic tools and concepts that aid in thesolution of the problems encountered in thatchapter.

In this self-contained resource, the material illus-trated extends from the basic elements of proba-bility to advanced multi-parameter maximum like-lihood-based methods for estimation and hypoth-esis testing. The book also includes highly practicalproblems based on real-life applications taken pre-dominantly from the health sciences.

Features

• Includes detailed solutions to every problem

• Serves as a supplemental source of a wide vari-ety of exercises for advanced undergraduateand graduate students in statistical theory andbiostatistics courses

• Contains problems drawn from real-life appli-cations in the health sciences

• Covers basic probability theory, along with uni-variate distribution theory, multivariate distribu-tion theory, estimation theory, and hypothesistesting theory

Catalog no. C7222, November 2010c. 428 pp., Soft CoverISBN: 978-1-58488-722-5, $49.95 / £24.99

New!

BiosurveillanceMethods and CaseStudiesEdited by

Taha Kass-HoutAtlanta, Georgia, USA

Xiaohui ZhangInternational Public HealthInstitute, Tucson, Arizona, USA

“… This text provides an important venue for thesharing of ideas and engagement of health scien-tists and practitioners that will be needed to assureprogress.”

—From the Foreword by Daniel M. Sosin, MD, MPH,Acting Director, Office of Public Health Preparedness

and Response, Centers for Disease Control andPrevention

Capturing the progress of modern-day pioneerswho are walking in John Snow’s footsteps, this vol-ume discusses how automated biosurveillance sys-tems churn through vast amounts of health-relat-ed data to support epidemiologists and publichealth officials in the early identification, situationawareness, and response management of naturaland man-made health-related events.Contributors share candid, first-hand insights onlessons learned and unresolved issues that willhelp chart the future of biosurveillance.

Features

• Provides a synopsis of current state-of-the-artpractices as well as a starting point for thedevelopment and evaluation of new methods

• Covers applied research and complete casestudies that focus on local, regional, national,and international implementation

• Presents techniques from other fields, such asintelligence and engineering

• Explores future innovations in biosurveillance,including advances in analytical methods,modeling, and simulation

• Addresses policy and organizational issuesrelated to the construction of biosurveillancesystems




27

Biostatistics


Design andAnalysis ofQuality of LifeStudies inClinical TrialsSecond EditionDiane L. FaircloughUniversity of Colorado HealthSciences Center, Denver, USA

Using SAS, SPSS, and R, this book addresses thestatistical methods for the design and analysis oflongitudinal studies. This edition includes a newchapter on testing models, a new chapter onQALYs and QTWiST, recent developments for theanalysis of trials with missing data, and revised dis-cussions of multiple comparisons procedures.Data sets, software code, and more are availableon the book’s website.


Data and SafetyMonitoringCommittees inClinical TrialsJay HersonJohns Hopkins University,Baltimore, Maryland, USA

“…Jay Herson provides a concise overview ofDMCs in a useful and accessible format. For some-one new to the area, this text will provide a valu-able introduction quickly and effectively. At thesame time, the presentation style will allow thosewith more knowledge to move through the materi-al expeditiously, and they will also benefit. …”

—Biometrics, March 2010


ClusterRandomisedTrialsRichard J. HayesLondon School of Hygiene &Tropical Medicine, UK

Lawrence H. MoultonJohns Hopkins Bloomberg Schoolof Public Health, Baltimore,Maryland, USA

“…This is a well-written book which I definitelyrecommend, especially as a textbook for graduateor postgraduate level studies, or as a referencebook for researchers working on the design oranalysis of CRTs. …”

—Journal of the Royal Statistical Society, Series A, Vol.173, Issue 1, January 2010

“… highly recommend this book for its unique andvery important strengths. …”

—Neil Klar, University of Western Ontario, Journal ofBiopharmaceutical Statistics, 2010, Issue 1


Sample Sizes for Clinical TrialsSteven A. JuliousUniversity of Sheffield, UK

“…this is an extremely useful reference book thatdoes not require a large investment of time to beable to put it to good use. The nomenclature usedis clear and not overly complex … he also coverssome less common topics, … which are very usefulin practice and somewhat unique as topics for atext on this subject matter.”

—Christopher A. Assaid, Journal of BiopharmaceuticalStatistics, Issue 4, 2010







Biostatistics

New!

Measures of InterobserverAgreement and ReliabilitySecond EditionMohamed M. ShoukriKing Faisal Specialist Hospital & Research Center, Riyadh,Saudi Arabia


“… an important strength of this text is that itbrings together technical results on agreement sta-tistics from a variety of sources, and it often pro-vides information about the precision of the esti-mates and interval estimates … a handy compila-tion of statistical approaches to interobserveragreement … biostatisticians …are likely to findthe summary and results to be helpful, and theywill want to add this book to their collection.”

—Patrick E. Shrout, New York University, Statistics inMedicine, Vol. 25, 2006

“Mohamed Shoukri is well placed to write thisbook, as he is one of the foremost currentresearchers in this field. I recommend it.”

—Journal of the Royal Statistical Society

“The well-written specialized book by Shoukri illus-trates the meaning and importance of the meas-ures of interobserver agreement with fun examples.…”—Journal of Statistical Computation and Simulation, Vol.

75, No. 4, April 2005

Emphasizing applications over theory, this booksurveys the method for evaluating inconsistenciesin findings from different observers and providesstandards and directions on how to run soundclinical and other types of studies. The authorpresents numerous practical examples andincludes SAS code to help with problem solving,both within the book and on the CRC website. Anextensive review of the literature offers access tothe latest developments in the field.

The new edition includes more detail on SAS,many new applications and tables, and updatedreferences.


MeasurementErrorModels, Methods,and ApplicationsJohn P. BuonaccorsiUniversity of Massachusetts,Amherst, Massachusetts, USA

This work describes the impacts of measurementerrors on naive analyses that ignore them andpresents ways to correct for them across a varietyof statistical models, from simple one-sampleproblems and misclassification in categorical mod-els to regression models to more complex mixedand time series models. The author includes exam-ples using real-world data from epidemiology,ecology, and other disciplines and employs SAS-IML and Stata to implement many of the tech-niques in the examples.


BayesianMethods forMeasures ofAgreementLyle D. BroemelingMedical Lake, Washington, USA

“This book is a welcome addition to the literatureon Bayesian inference as it presents methods forthe design and analysis of agreement studies. …The approach presented by the author is novel andthe novice will find a helpful introduction toBayesian inference in an appendix. … a valuablereference source. For those unfamiliar withWinBUGS, the author introduces the fundamentalsof programming and executing BUGS.”






29

Biostatistics


Bayesian MissingData ProblemsEM, DataAugmentation andNoniterativeComputationMing T. TanUniversity of Maryland,Baltimore, USA

Guo-Liang Tian and KaiWang NgUniversity of Hong Kong, People’s Republic of China

This book presents solutions to missing data prob-lems through explicit or noniterative sampling cal-culation of Bayesian posteriors, based on theinverse Bayes formulae. The authors focus onexact numerical solutions, a conditional samplingapproach via data augmentation, and a nonitera-tive sampling approach via EM-type algorithms.They describe Monte Carlo simulation, numericaltechniques, and optimization methods. They illus-trate the methods with biostatistical models andreal-world applications.


Multiple TestingProblems inPharmaceuticalStatisticsEdited by

Alex DmitrienkoEli Lilly and Company,Indianapolis, Indiana, USA

Ajit C. TamhaneNorthwestern University,Evanston, Illinois, USA

Frank BretzNovartis Pharma AG, Basel, Switzerland

“If you are … looking for a comprehensive descrip-tion of multiple testing in a clinical trial, this bookis for you. … we would rank it as the best book onmultiplicity given its up-to-date material … anexcellent guide for those who find themselves faceto face with simultaneous testing and would like tohave an overview over possible ways of tacklingthe problem. …”

—Vera Lisovskaja and Carl-Fredrik Burman, Journal ofBiopharmaceutical Statistics, Issue 6, 2010


Missing Data inLongitudinalStudiesStrategies forBayesian Modelingand SensitivityAnalysisMichael J. DanielsUniversity of Florida, Gainesville,USA

Joseph W. HoganBrown University, Providence, Rhode Island, USA

“… [the authors] have gone further than anyoneelse in developing methods for the NMAR case. …an excellent introduction and a first-rate treatmentof cutting-edge topics. …”

—Paul D. Allison, University of Pennsylvania,Significance, September 2010

“This text is the only Bayesian textbook that pro-vides a contemporary and comprehensive treatmentof Bayesian approaches to a common and criticallyimportant topic. … I strongly endorse this book.”

—Sharon-Lise Normand, Harvard School of PublicHealth, Boston, Massachusetts, USA


New!

An Introductionto Stata forHealthResearchersThird EditionSvend Juul and MortenFrydenbergAarhus University, Denmark

Incorporating the new features of Stata 11, thisthird edition continues to systematically coverdata management, simple description and analy-sis, and more advanced analyses that are oftenused in health research. It also describes manygraph types as well as how to modify the appear-ance of a graph. This edition presents the new,flexible syntax for factor variables and includesrewritten chapters on regression and survivalanalysis. Download robust data sets from thebook’s website.

Catalog no. N10327, August 2010, 340 pp.Soft Cover, ISBN: 978-1-59718-077-1$79.95 / £49.99






Statistics for Social and Behavioral Sciences

Applied SurveyData AnalysisSteven G. Heeringa,Brady T. West, andPatricia A. BerglundUniversity of Michigan, AnnArbor, USA

With many examples and exercises based onmajor real-world survey data sets, this book pro-vides a practical statistical overview of the analysisof complex sample survey data. Drawing on theauthors’ extensive teaching, consulting, andresearch experiences, it also supplies a usefulframework for integrating more in-depth studiesof the theory and methods of survey data analysis.

The authors emphasize methods and workedexamples using available software procedureswhile reinforcing the principles and theory thatunderlie those methods.

Features

• Demonstrates how design characteristics, suchas stratification, clustering, and weighting, areeasily incorporated into the statistical methodsand software for survey estimation and infer-ence

• Presents many methods and models for surveydata analysis, including the linear regression,generalized linear, Cox proportional hazards,and discrete time models

• Explores developments in advanced statisticaltechniques, such as multilevel analysis of surveydata

• Supplies advice and recommendations basedon the authors’ experiences as well as currentthinking on best practices

• Uses theory boxes to develop or explain a fun-damental theoretical concept underlying statis-tical methods

• Offers software code, brief technical reports,links to example survey data sets, and more onthe book’s website


New!

Randomized Response andIndirect QuestioningTechniques in SurveysArijit ChaudhuriIndian Statistical Institute, Calcutta, India

A long-standing problem in survey research is thatrespondents are often reluctant to give truthfulanswers to sensitive questions. In this book, one ofthe world’s leading experts on the subject sum-marizes the current state of the theory and prac-tice of the randomized response technique, whichguarantees respondents’ anonymity and mini-mizes their discomfort. The text examines how toextend the theory to situations employingunequal probability sampling.


New!

NonlinearDynamicalSystems Analysisfor theBehavioralSciences UsingReal DataEdited by

Stephen J. GuastelloPewauku, Wisconsin, USA

Robert A.M. GregsonAustralian National University, Canberra

Reflecting the expertise of the major contributorsto NDS psychology, this compilation of researchmethods examines the techniques that haveproven to be most useful in the behavioral sci-ences. The book develops the skills and expertisein framing hypotheses dynamically and in buildingviable analytic models to test them. It addressestopics and methods of current interest in an appli-cation-driven manner.

Catalog no. K11053, November 2010, c. 638 pp.ISBN: 978-1-4398-1997-5, $129.95 / £82.00




31

Statistics for Social and Behavioral Sciences


Linear CausalModeling withStructuralEquationsStanley A. MulaikGeorgia Institute of Technology,Atlanta, USA

Emphasizing causation as a functional relationshipbetween variables, this book provides comprehen-sive coverage on the basics of SEM. It discusses thehistory and philosophy of causality, explains howthe algorithms in SEM are derived and how theywork, covers various indices and tests for evaluat-ing the fit of structural equation models to data,and explores recent research in graph theory, pathtracing rules, and model evaluation.

Catalog no. K10039, 2009, 468 pp.ISBN: 978-1-4398-0038-6, $79.95 / £48.99

Textbook

MultivariableModeling andMultivariateAnalysis for theBehavioralSciencesBrian S. EverittKing’s College, University ofLondon, UK

“… The first two chapters give a magnificent intro-duction before approaching the modeling issues.… among the best I have ever seen in books onmultivariate methods. … He also goes well beyondthe typical graphs showing how to explore realinsights of the data. … Putting the R code in anappendix and on the website is an excellent choice.… I’ll be happy to recommend this book to stu-dents and researchers.”


Includes online solutions, datasets, and code

Catalog no. K10396, January 2010, 320 pp.Soft Cover, ISBN: 978-1-4398-0769-9$69.95 / £29.99

Textbook

Foundations ofFactor AnalysisSecond EditionStanley A. MulaikGeorgia Institute of Technology,Atlanta, USA

Providing a practical, thorough understanding ofhow factor analysis works, this long-awaited sec-ond edition includes a new chapter on the multi-variate normal distribution, its general properties,and the concept of maximum-likelihood estima-tion. It also contains a rewritten chapter on ana-lytic oblique rotation as well as a revised chapteron confirmatory factor analysis. This edition offersmore complete coverage of descriptive factoranalysis and doublet factor analysis and exploresthe developments of factor score indeterminacy.

Catalog no. K10005, January 2010, 548 pp.ISBN: 978-1-4200-9961-4, $79.95 / £39.99

Textbook

Analysis ofMultivariateSocial ScienceDataSecond EditionDavid J. Bartholomew,Fiona Steele, Irini Moustaki, and Jane Galbraith

“… Written by some of the leaders in the field, thesecond edition expands the horizon of the first edi-tion by three new chapters. … The book shouldprovide a superb introduction to these methods forgraduate students … Good examples abound[and] … so do worked-out applications. … Thewebsite is a treasure trove … the book is essentialto read … .”

—Tim Futing Liao, University of Illinois, Journal of theRoyal Statistical Society, Series A, 2010

Includes online solutions, software, and datasets







Environmental Statistics

New!

Local Models forSpatial AnalysisSecond EditionChristopher D. LloydQueen’s University, Belfast,Northern Ireland, UK

With worked examples and case studies, this sec-ond edition describes a wide range of methodsthat account for local variations in geographicalproperties. It presents additional material on geo-graphically weighted statistics and local regressionapproaches, a more detailed overview of localmodels with reference to recent critical reviewsabout the subject, expanded coverage of individ-ual methods and connections between them, andaccess to online resources that support learning.


Textbook

Statistics forEnvironmentalScience andManagementSecond EditionBryan F.J. ManlyWestern EcoSystem Technology,Inc., Laramie, Wyoming, USA

Presenting a nonmathematical approach to thistopic, this book introduces frequently used statisti-cal methods and practical applications for theenvironmental field. This second edition featuresupdated references and examples along with newand expanded material on data quality objectives,the generalized linear model, spatial data analysis,and Monte Carlo risk assessment.


Textbook

Environmentaland EcologicalStatistics with RSong S. QianNicholas School of theEnvironment, Duke University,Durham, North Carolina, USA

Emphasizing the inductive nature of statisticalthinking, this text connects applied statistics to theenvironmental and ecological fields. It follows thegeneral approach to solving a statistical modelingproblem, covering model specification, parameterestimation, and model evaluation. The author usesmany examples to illustrate the statistical modelsand presents R implementations of the models.The data sets and R scripts used in the book alongwith exercises and solutions are available online.

Catalog no. C6206, January 2010, 440 pp.Soft Cover, ISBN: 978-1-4200-6206-9$79.95 / £49.99

Bayesian Analysisfor PopulationEcologyRuth King, Byron J.T. Morgan, Olivier Gimenez, andStephen P. Brooks

“… a solid introduction to Bayesian modeling. …The examples are interesting and do not hinderthose not in the discipline of population ecologyfrom understanding the explanation of the statisti-cal principles being discussed. … The reader is notexpected to have a prior knowledge of Bayesianmodeling, nor is there an assumption that readersare familiar with R or WinBUGS. …”—Journal of Statistical Software, August 2010, Volume

36






33

Statistics in Genetics, Bioinformatics, and Computational Biology


New!

BayesianModeling inBioinformaticsEdited by

Dipak K. DeyUniversity of Connecticut, Storrs,USA

Samiran GhoshIndiana University-Purdue University, Indianapolis, USA

Bani K. MallickTexas A&M University, College Station, USA

This volume discusses the development and appli-cation of Bayesian statistical methods for theanalysis of high-throughput bioinformatics dataarising from problems in molecular and structuralbiology and disease-related medical research, suchas cancer. It presents a broad overview of statisti-cal inference, clustering, and classification prob-lems in two main high-throughput platforms:microarray gene expression and phylogenic analy-sis.

Focusing on design, statistical inference, and dataanalysis from a Bayesian perspective, the bookexplores statistical challenges in bioinformaticsdata analysis and modeling and offers solutions tothese problems. It encourages readers to draw onthe evolving technologies and promote statisticaldevelopment in this area of bioinformatics.

Features

• Discusses the design, statistical inference, andanalysis of data sets arising from high-through-put experiments

• Presents a variety of recently developedBayesian techniques

• Covers applications in genome-wide studies,phylogenetics, breast cancer, expressiongenomics, and more

• Illustrates concepts using real-world data

• Provides software illustrations for complicatedprocedures

Catalog no. C7017, September 2010, 466 pp.ISBN: 978-1-4200-7017-0, $89.95 / £57.99

New!

Clustering inBioinformaticsand DrugDiscoveryJohn D. MacCuish andNorah E. MacCuishMesa Analytics & Computing,Inc., Santa Fe, New Mexico, USA

“…Those of us who learned their clustering fromAnderberg, Sokal and Sneath, and Willett nowhave a valuable additional resource suitable forthe 21st century.”

—From the Foreword by John Bradshaw, Barley,Hertfordshire, UK

With a DVD of color figures, this book provides anexpert guide on extracting the most pertinentinformation from pharmaceutical and biomedicaldata. The authors include many real-world exam-ples from industrial settings, such as combinatori-al library design and compound databases.


R ProgrammingforBioinformaticsRobert Gentleman

“This is a very excellent book. … the best hand-book on R programming that is currently avail-able. …”

—Journal of Statistical Software

This practical guide focuses on the programmingskills needed to use R for the solution of bioinfor-matics and computational biology problems. Itcovers object-oriented programming in R, datamark-up and web services languages and tools,and string handling and manipulations. The com-plete R source code is available on the book’s web-site.






Statistics in Genetics, Bioinformatics, and Computational Biology

New!

Methods inMedicalInformaticsFundamentals ofHealthcareProgramming inPerl, Python, andRubyJules J. BermanColumbia, Maryland, USA

A user friendly, step-by-step practical guide forapplying basic informatics algorithms to medicaldata sets, this book includes examples using Perl,Python, and Ruby. The author employs a minimalselection of commands for quick learning and ref-erences only free, publicly available resources. Thebook demonstrates how easy it is to master thewide variety of data types encountered in a health-care setting with just a few simple programmingcommands.


Gene ExpressionStudies UsingAffymetrixMicroarraysHinrich Gohlmann andWillem TalloenJohnson & Johnson, Beerse,Belgium

This work tears down the omnipresent languagebarriers among molecular biology, bioinformatics,and biostatistics researchers by explaining theentire process of a gene expression study fromconception to interpretation. Along with illustra-tive examples using R and BioConductor, it pres-ents important technical and statistical pitfalls andproblems. The authors show how to optimizeexperiments and data analysis using Affymetrix aswell as other microarray platforms.


MicroarrayImage AnalysisAn AlgorithmicApproachKarl Fraser, ZidongWang, and Xiaohu LiuBrunel University, Uxbridge,Middlesex, UK

To harness the high-throughput potential of DNAmicroarray technology, it is crucial that the analy-sis stages of the process are decoupled from therequirements of operator assistance. This bookpresents an automatic system for microarrayimage processing to make this decoupling a reali-ty. The proposed system integrates and extendstraditional analytical-based methods and custom-designed novel algorithms. The text includesdetails of the algorithmic processes along with ananalysis of the processes performance over real-world microarray image data.


DNA MethylationMicroarraysExperimental Designand StatisticalAnalysisSun-Chong WangNational Central University,Chungli Taoyuan, Taiwan

Art PetronisCentre for Addiction and MentalHealth, Toronto, Ontario, Canada

“…a consistent and self-contained overview onimportant fundamental and modern proceduresused by researchers in biology, bioinformatics,experimental designs …”

—Cryssoula Ganatsiou, Zentralblatt MATH 1172

“…This book is a helpful guide for researchers andstudents with an interest in performing genomicstudies using high-throughput microarrays. … Awide range of useful data analysis tools are cov-ered …”

—Biometrics, March 2009






35

Statistics in Genetics, Bioinformatics,and Computational Biology


Textbook

Statistics inHuman Geneticsand MolecularBiologyCavan ReillyUniversity of Minnesota,Minneapolis, USA

Focusing on the roles of different segments ofDNA, this text provides a basic understanding ofproblems arising in the analysis of genetics andgenomics. With many worked examples and end-of-chapter exercises, it presents statistical applica-tions in genetic mapping, DNA/protein sequencealignment, and analyses of gene expression datafrom microarray experiments. The text also dis-cusses differential gene expression detection aswell as classification and cluster analysis usinggene expression data sets.


New!Textbook

Introduction to StatisticalData Analysis for the LifeSciencesClaus Thorn Ekstrom andHelle SorensenUniversity of Copenhagen, Denmark

Developed from the authors’ courses, this textprovides a computational toolbox that enablesreaders to perform actual analysis for real data setsas well as the confidence and skills needed toundertake more sophisticated analyses as theircareers progress. While the main text can be usedwith any statistical software, the authors encour-age a reliance on R. Data sets are available on asupporting website.Solutions manual available for qualifying instructors

Catalog no. K11221, August 2010, 427 pp.Soft Cover, ISBN: 978-1-4398-2555-6$69.95 / £31.99

Meta-analysisand CombiningInformation inGenetics andGenomicsEdited by

Rudy GuerraRice University, Houston, Texas,USA

Darlene R. GoldsteinEPFL SB IMA STAT, Switzerland

This book provides many novel techniques foranalyzing data from modern biological studiesthat involve multiple data sets, either of the sametype or multiple data sources. It examines theproblems that occur when identifying commondisease or quantitative trait loci across differentstudies and explores the combination of datasources, including genotype, gene expression,protein, and DNA sequence data.

Catalog no. C522X, January 2010, 360 pp.ISBN: 978-1-58488-522-1, $99.95 / £63.99

New!

Introduction toData Analysiswith R forForensicScientistsJames Michael CurranUniversity of Auckland, NewZealand

This book provides researchers with the dexteritynecessary to systematically analyze data discov-ered from the fruits of their research. It includes arefresher on basic statistics, an introduction to R,techniques for the visual display of data throughgraphics, an overview of statistical hypothesistests, a comprehensive guide to the use of the lin-ear model, an introduction to extensions to thelinear model for commonly encountered scenar-ios, and instruction on how to plan and designexperiments.

Catalog no. 88262, July 2010, 331 pp.ISBN: 978-1-4200-8826-7, $99.95 / £42.00

Statistics for Biological Sciences






Statistics for Biological Sciences

Coming soon!Textbook

Modelling and QuantitativeMethods in FisheriesSecond EditionMalcolm HaddonUniversity of Tasmania, Australia

Revised and restructured, Modelling andQuantitative Methods in Fisheries, SecondEdition provides an accessible introduction toquantitative methods in fisheries. This edition fea-tures new material on tests and comparisons aswell as new chapters on length-based models andestimating uncertainty using Bayesian methods.

The text takes a structured, step-by-step approachthat introduces the material in a logical sequence.It covers a range of topics, such as simple linearregression, complex nonlinear modeling, method-ology, and specific fields in fisheries.

The book also includes numerous real-worldexamples implemented in Excel, with workbooksfor all examples available for download on theweb.

Features

• Provides new chapters on length-based modelsand estimating uncertainty using Bayesianmethods

• Presents a structured, step-by-step approachthat covers material in a logical sequence

• Includes numerous real-world examples implemented in Excel, allowing users to applymethods to their own data

• Covers a large number of topics, from simplelinear regression to complex nonlinear modeling

• Offers downloadable Excel workbooks for allexamples on a supporting website

Catalog no. C561X, January 2011, c. 416 pp.ISBN: 978-1-58488-561-0, $79.95 / £39.99

New!Textbook

An Introduction to StochasticProcesses with Applications toBiologySecond EditionLinda J.S. AllenTexas Tech University, Lubbock, USA

Emphasizing applications in biology, this secondedition of a bestseller enables a complete under-standing of stochastic formulation. This editioncontains a new chapter on the biological applica-tions of stochastic differential equations and newsections on alternative methods for derivation of astochastic differential equation, data and parame-ter estimation, Monte Carlo simulation, and more.

The book provides a comprehensive, easy-to-fol-low introduction to the basic theory and numer-ous biological applications of stochastic processes.It is organized according to the three types of sto-chastic processes: discrete time Markov chains,continuous time Markov chains, and continuoustime and state Markov processes. The authorincludes MATLAB® throughout to help with thesolutions of various problems.

Features

• Takes readers step-by-step through well-knownbiological models

• Includes a wealth of examples, diagrams, andfigures as well as end-of-chapter exercises

• Covers probability, Markov chains, discretetime branching processes, population dynam-ics, epidemiology, and birth and death chains

• Encourages the use of MATLAB programs tovisualize and understand the dynamics of vari-ous stochastic processes

• Requires only a basic background in probabilitytheory, linear algebra, and analysis





37

Statistics in Engineering and Physical Science


New!Textbook

TransportationStatistics andMicrosimulationClifford H. SpiegelmanTexas A&M University, CollegeStation, USA

Eun Sug ParkTexas Transportation Institute,College Station, USA

Laurence R. RilettUniversity of Nebraska, Lincoln, USA

By discussing statistical concepts in the context oftransportation planning and operations, this bookprovides the necessary background for makinginformed transportation-related decisions. Itexplains the why behind standard methods anduses real-world transportation examples and prob-lems to illustrate key concepts.

Classroom-tested at Texas A&M University, thetext covers the statistical techniques most fre-quently employed by transportation and pave-ment professionals. To familiarize readers with theunderlying theory and equations, it contains prob-lems that can be solved using statistical software,such as SAS’s JMP package. Students can buy theirown copy of JMP at a reduced price via a postcardin the book.

Features

• Includes realistic transportation-related prob-lems that draw on data from various U.S. trans-portation studies

• Compares planned experiments, quasi-experi-ments, and field studies

• Presents strategies for conducting computer-aided statistical designs, fractional factorialdesigns, and screening designs

• Emphasizes bias-corrected confidence intervals

• Covers resampling techniques for evaluatinguncertainties, including the jackknife and boot-strap

• Takes a conjugate prior approach to Bayesianestimation

• Discusses smoothing estimators in both regres-sion and density estimation


New!Textbook

Statistical andEconometricMethods forTransportationData AnalysisSecond EditionSimon P. WashingtonUniversity of California, Berkeley, USA

Matthew G. KarlaftisNational Technical University of Athens, Greece

Fred L. ManneringPurdue University, West Lafayette, Indiana, USA


“It is well done and well organized, and providesgood coverage of all the essential elements of sta-tistical and econometric methods and modelsapplied to transportation … I would highly recom-mend it to anyone engaged in transportationresearch. I suspect it will be the definitive text onstatistics in transportation for some years to come… I am pleased to have had the opportunity toread the book and look forward to using it in mywork in the future.”

—Technometrics, November 2004

Now in its second edition, this book continues todescribe the techniques most useful for modelingthe many complex aspects of transportation. Itpresents the statistical fundamentals, continuousdependent variable models, count and discretedependent variable models, and Bayesian statisti-cal modeling. Data sets are available for downloadat www.crcpress.com

This edition features new chapters on mixed logitmodels, logistic regression, and ordered probabil-ity models. It also offers additional coverage onBayesian inference and MCMC methods. Aftermastering this material, readers should be able toformulate research hypotheses, identify appropri-ate statistical and econometric models, avoidcommon pitfalls and misapplications of statisticalmethods, and interpret model results correctly.

Catalog no. C285X, December 2010c. 600 pp., ISBN: 978-1-4200-8285-2$99.95 / £63.99




Statistics in Engineering and Physical Science

AcceptanceSampling inQuality ControlSecond EditionEdward G. SchillingRochester Institute ofTechnology, New York, USA

Dean V. NeubauerCorning Incorporated,Horseheads, New York, USA

“… This new edition continues to be equally usefulfor both practitioners and researchers in the arenaof statistical quality control. … a nice addition toyour personal library!”

—Technometrics, Vol. 51, No. 3, August 2009

“Schilling’s first edition of Acceptance Sampling inQuality Control is a classic, and is considered bymany as a ‘must-have book’ for anyone working inquality control. …”—Journal of Quality Technology, Vol. 41, No. 4, October

2009


New!

Statistical Process Control forReal-World ApplicationsWilliam A. LevinsonLevinson Productivity Systems, Wilkes-Barre, Pennsylvania,USA

This book explains how to deal with non-normalapplications scientifically and to elucidate themethodology to suppliers and customers. It showshow to handle uncooperative real-world processesthat do not follow normal assumptions. The textexplains how to set realistic control limits and cal-culate meaningful process capability indices fornon-normal applications. It highlights the pitfallsof assuming normality for all processes.


Textbook

Modeling andAnalysis ofStochasticSystemsSecond EditionVidyadhar G. KulkarniUniversity of North Carolina,Chapel Hill, USA

This text covers the most important classes of sto-chastic processes used in the modeling of diversesystems. Along with new appendices that collectresults from analysis and differential and differenceequations, this edition contains a new chapter ondiffusion processes with applications to finance.MATLAB®-based programs can be downloadedfrom the author’s website.Solutions manual available for qualifying instructors


AnalyticalMethods for RiskManagementA SystemsEngineeringPerspectivePaul R. GarveyThe MITRE Corporation, Bedford,Massachusetts, USA

Using numerous examples to illustrate real-worldengineering system projects, this book presentsthe foundation processes and analytical practicesfor identifying, analyzing, measuring, and manag-ing risk in traditional systems, systems-of-systems,and enterprise systems. It describes asupplier–provider framework to model and meas-ure risk in engineering enterprise systems andsummarizes success factors for managing risk inthe engineering of systems.






“This fine book represents the most recentand exciting developments in this area, andgives ample justification for the power andelegance of Bayesian trial design andanalysis. …”—From the Foreword by David J. Spiegelhalter,

MRC Biostatistics Unit, University ofCambridge, UK

Written by leading pioneers of Bayesianclinical trial designs, this up-to-date toolkitof Bayesian techniques for clinical trialdesign and analysis:

• Covers the design of Phase I, II, and IIIclinical trials

• Establishes basic principles beforeextending them to specific phases andendpoints

• Includes R and WinBUGS codes andother materials on supporting websites

Catalog no. K11217, July 2010323 pp., ISBN: 978-1-4398-2548-8$89.95 / £57.99

A Complete Reference for ImplementingAdaptive Design and Analysis inPharmaceutical/Clinical Research

• Gives a well-balanced summary of current regulatory perspectives

• Presents real-world examples of a range ofadaptive designs, including an adaptive dose-escalation design for early phase cancertrials, a two-stage seamless Phase I/II design fora hepatitis C virus trial, and a biomarker designfor targeted clinical trials

• Describes the latest developments and bestpractices

• Examines the role of an independent data safety monitoring board

• Discusses the importance of sample size estimation/allocation, justification, and adjustment when implementing a complicated adaptive design

Catalog no. K10507, November 2010496 pp., ISBN: 978-1-4398-1016-3$99.95 / £63.99

For more information on these books visit www.crcpress.com



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