Contents Introductory Statistics ......................................3 Statistical Theory & Methods............................5 Biostatistics ....................................................12 Page 7
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Computational Statistics ................................17 Data Mining and Machine Learning................20 Statistics for Psychology, Social Science & Law ......................................22 Environmental & Ecological Statistics..............24 Statistical Genetics & Bioinformatics ..............25
Page 10
Page 14
Statistics for Business, Finance & Economics ..................................................28 Statistics for Engineering, Reliability and Quality Control ........................................30
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MBCST10 MC_3.9.10rd
Introductory Statistics An Introduction to Statistical Inference and Its Applications with R
Introduction to Probability with R
Michael W. Trosset
Kenneth Baclawski
Indiana University, Bloomington, USA
Northeastern University, Boston, Massachusetts, USA
Emphasizing concepts rather than recipes, An Introduction to Statistical Inference and Its Applications with R provides a clear exposition of the methods of statistical inference for students who are comfortable with mathematical notation. Numerous examples, case studies, and exercises are included. R is used to simplify computation, create figures, and draw pseudorandom samples—not to perform entire analyses.
Read the Reviews:
After discussing the importance of chance in experimentation, the text develops basic tools of probability. The plug-in principle then provides a transition from populations to samples, motivating a variety of summary statistics and diagnostic techniques. The heart of the text is a careful exposition of point estimation, hypothesis testing, and confidence intervals. The author then explains procedures for 1- and 2-sample location problems, analysis of variance, goodness-of-fit, and correlation and regression. He concludes by discussing the role of simulation in modern statistical inference. Focusing on the assumptions that underlie popular statistical methods, this book explains how and why these methods are used to analyze experimental data. Contents: Experiments. Mathematical Preliminaries. Probability. Discrete Random Variables. Continuous Random Variables. Quantifying Population Attributes. Data. Lots of Data. Inference. 1-Sample Location Problems. 2-Sample Location Problems. The Analysis of Variance. Goodness-of-Fit. Association. Simple Linear Regression. Simulation-Based Inference. R: A Statistical Programming Language.
"… I was very impressed with this text. It gives a sold introduction to probability with many interesting applications. One of its strengths is its material on stochastic processes." – Jim Albert, Bowling Green State University, in The American Statistician, Vol. 63, No. 2
"… a welcome addition … clearly written and very well-organized …" —Journal of Statistical Software
"… a pleasure to read … All programs of the book, and several others, are downloadable from the book’s website. … the exercises of this book are a lot of fun! … Another aspect in which the book stands out among the competition is that discrete probability gets its due treatment. …" —Miklós Bóna, University of Florida, MAA Reviews
Based on the popular course taught at MIT by Gian-Carlo Rota, the book offers R programs and web links on a supplementary web site. Contents: Sets, Events, and Probability. Finite Processes. Discrete Random Variables. General Random Variables. Statistics and the Normal Distribution. Conditional Probability. The Poisson Process. Randomization and Compound Processes. Entropy and Information. Markov Chains. Appendices. References. Index. Catalog no. C6521, 2008, 384 pp., ISBN: 978-1-4200-6521-3, $89.95 / £39.99
Catalog no. C9470, 2009, 496 pp., ISBN: 978-1-58488-947-2, $79.95 / £48.99
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Introductory Statistics New!
Introduction to Probability with Mathematica®
Applied Stochastic Modelling
Second Edition
Second Edition
Kevin J. Hastings
Byron J.T. Morgan
Knox College, Galesburg, Illinois, USA
University of Kent, UK
This second edition shows how to easily create simulations from templates and solve problems using Mathematica® 7.0. Along with new sections on order statistics, transformations of multivariate normal random variables, and Brownian motion, this edition offers an expanded section on Markov chains, more example data of the normal distribution, and more attention on conditional expectation. It also includes additional problems from Actuarial Exam P and the accompanying CDROM contains updated Mathematica notebooks. Catalog no. C7938, January 2010, 465 pp., ISBN: 978-1-4200-7938-8, $89.95 / £57.99
New!
Read the Reviews: "… covers much ground in quite a short space … I like this book and strongly recommend it … " —Tim Auton, Journal of the Royal Statistical Society
" …very well written, fresh in its style, with lots of wonderful examples and problems." —R.P. Dolrow, Technometrics
"A useful tool for both applied statisticians and stochastic model users of other fields, such as biologists, sociologists, geologists, and economists." —Zentralblatt MATH
Catalog no. C6668, 2009, 368 pp., Soft Cover, ISBN: 978-1-58488-666-2, $59.95 / £29.99
Probability and Statistics with R
Stochastic Processes
Maria Dolores Ugarte and Ana F. Militino
An Introduction, Second Edition
Public University of Navarre, Pamplona, Spain
Peter Watts Jones and Peter Smith
Alan T. Arnholt
Keele University, Staffordshire, UK
Appalachian State University, Boone North Carolina, USA
Using Mathematica® and R, this updated text discusses the modeling and analysis of random experiments using the theory of probability. It illustrates discrete random processes through the classical gambler’s ruin problem and its variants. It also covers continuous random processes, such as Poisson and general population models. With over 50 worked examples and more than 200 end-of-chapter problems, the text describes applications of probability to modeling problems in engineering, medicine, and biology.
"… comprehensive and well written. The notation is clear and the mathematical derivations behind nontrivial equations and computational implementations are carefully explained … wellbalanced mix of theory, examples and R code."
Catalog no. K10004, January 2010, 232 pp., Soft Cover, ISBN: 978-1-4200-9960-7, $79.95 / £34.99
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—The American Statistician
“… an impressive book … a good reference book with comprehensive coverage of the details of statistical analysis and application that the social researcher may need in their work. I would recommend it as a useful addition to the bookshelf." —Significance
Catalog no. C8911, 2008, 728 pp., ISBN: 978-1-58488-891-8, $89.95 / £49.99
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Statistical Theory and Methods New!
New!
Linear Model Methodology André I. Khuri Supported by a large number of examples, this book provides a strong foundation in the theory of linear models and explores the latest developments in data analysis. It encompasses a wide variety of topics in linear models that incorporate the classical approach and more recent trends and modeling techniques. The author emphasizes the central role matrices have played in the modern development of linear models and presents a unified approach to modeling discrete and continuous response data. Catalog no. C4819, January 2010, 562 pp., ISBN: 978-1-58488-481-1, $99.95 / £63.99
Visualizing Data Patterns with Micromaps Daniel B. Carr George Mason University, Fairfax, Virginia, USA
Linda Williams Pickle StatNet Consulting, LLC., Gaithersburg, Maryland, USA
"… extremely well written … It is obvious that the authors are in total command of the topic and bring years of experience … The authors understand what areas need special attention and explanation … the text is illustrative and entertaining. The limitations of micromaps are known and discussed. The reader gains a good understanding of what they are for and what they can and cannot accomplish." —Oliver Schabenberger, SAS Institute Inc., Cary, North Carolina, USA
Catalog no. C7573, April 2010, c. 168 pp., ISBN: 978-1-4200-7573-1, $69.95 / £44.99
New!
New!
Expansions and Asymptotics for Statistics
Applied Statistical Inference with MINITAB
Christopher G. Small
Sally A. Lesik
University of Waterloo, Ontario, Canada
Central Connecticut State University, New Britain, USA
This book provides a broad toolkit of analytical methods and implements the topics with relevant Maple™ commands. It first presents methods for expansions of functions arising in probability and statistics. The text then describes mainstream statistical asymptotics, namely the asymptotic normality and asymptotic efficiency of standard estimators as the sample size goes to infinity. After focusing on Laplace approximation and the saddle-point method, the author discusses alternatives to Monte Carlo techniques, such as the summation of series.
Through clear, step-by-step mathematical calculations, this text provides a solid understanding of how to apply statistical techniques in practice using MINITAB. It focuses on the concepts of confidence intervals, hypothesis testing, validating model assumptions, and power analysis, taking an introductory, practical approach to statistics. It establishes the foundation for readers to build on work in more advanced inferential statistics. Data sets and a trial version of MINITAB are included on accompanying CD-ROMs.
Catalog no. C5904, May 2010, c. 357 pp., ISBN: 978-1-58488-590-0, $89.95 / £57.99
Catalog no. C6583, January 2010, 464 pp., ISBN: 978-1-4200-6583-1, $89.95 / £54.99
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5
Statistical Theory and Methods Analysis of Messy Data Volume 1
New!
Design and Analysis of Experiments with SAS
Designed Experiments, Second Edition
John Lawson
George A. Milliken and Dallas E. Johnson
Brigham Young University, Provo, Utah, USA
A culmination of the author’s many years of consulting and teaching, this book provides practical guidance on the computer analysis of experimental data. It connects the objectives of research to the type of experimental design required, describes the actual process of creating the design and collecting the data, shows how to perform the proper analysis of the data, and illustrates the interpretation of results. Drawing on a variety of application areas, from pharmaceuticals to machinery, the book presents numerous examples of experiments and exercises that enable students to perform their own experiments. Harnessing the capabilities of SAS 9.2, it includes examples of SAS data step programming and IML, along with procedures from SAS Stat, SAS QC, and SAS OR. The text also shows how to display experimental results graphically using SAS ods graphics. The author emphasizes how the sample size, the assignment of experimental units to combinations of treatment factor levels, and the selection of treatment factor combinations affect the resulting variance and bias of estimates as well as the validity of conclusions. This text covers classical ideas in experimental design and the latest research topics, clearly discussing the practical aspects of creating a design, performing experiments, and interpreting the results of computer data analysis. Catalog no. C6060, April 2010, c. 594 pp., ISBN: 978-1-4200-6060-7, $99.95 / £63.99
Kansas State University, Manhattan, Kansas, USA
"… Every chapter has been systematically rewritten for greater clarity, and added explanatory material has been inserted throughout. Many new diagrams and redrawn diagrams have been provided; those that show how to lay out the experimental designs are just superb and extraordinarily clear. … highly recommended …" —International Statistical Review, 77, 2
Written by two long-time researchers and professors, this second edition has been fully updated to reflect the many developments that have occurred since the original publication.
New to the Second Edition • Several modern suggestions for multiple comparison procedures
• Additional examples of split-plot designs and repeated measures designs
• The use of SAS-GLM to analyze an effects model
• The use of SAS-MIXED to analyze data in random effects experiments, mixed model experiments, and repeated measures experiments The book explores various techniques for multiple comparison procedures, random effects models, mixed models, split-plot experiments, and repeated measures designs. The authors implement the techniques using several statistical software packages and emphasize the distinction between design structure and the structure of treatments. They introduce each topic with examples, follow up with a theoretical discussion, and conclude with a case study. Bringing a classic work up to date, this edition continues to show readers how to effectively analyze real-world, nonstandard data sets. Catalog no. C3340, 2009, 674 pp., ISBN: 978-1-58488-334-0, $89.95 / £54.99
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Statistical Theory and Methods New!
A Primer on Linear Models
Mixed Effects Models for Complex Data
John F. Monahan
Lang Wu
North Carolina State University, Raleigh, USA
University of British Columbia, Vancouver, Canada
"… very nice, very readable, and in particular I like the idea of avoiding leaps in the development and proofs, or referring to other sources for the details of the proofs. This is a useful well-written instructive book."
Presenting effective approaches to address missing data, measurement errors, censoring, and outliers in longitudinal data, this book covers linear, nonlinear, generalized linear, nonparametric, and semiparametric mixed effects models. It links each mixed effects model with the corresponding class of regression model for cross-sectional data and discusses computational strategies for likelihood estimations of mixed effects models. The author briefly describes generalized estimating equations methods and Bayesian mixed effects models and explains how to implement standard models using R and S-Plus.
—International Statistical Review
"This work provides a brief, and also complete, foundation for the theory of basic linear models …" —Nicoleta Breaz, in Zentralblatt Math
“… well written … references for researchers who would like to review the theory of linear models." —Journal of Biopharmaceutical Statistics, Issue 3
Catalog no. C6201, 2008, 304 pp., Soft Cover, ISBN: 978-1-4200-6201-4, $49.95 / £27.99
Catalog no. C7402, January 2010, 431 pp., ISBN: 978-1-4200-7402-4, $89.95 / £57.99
New!
Logistic Regression Models Joseph M. Hilbe Jet Propulsion Laboratory, California Institute of Technology, Pasadena, USA and Arizona State University, Tempe, USA
An overview of logistic models, including binary, proportional, ordered, and categorical response regression procedures, this text illustrates how to apply the models to medical, health, environmental/ecological, physical, and social science data. Stata is used to develop, evaluate, and display most models while R code is given at the end of most chapters. The author examines the theoretical foundation of the models and describes how each type of model is established, interpreted, and evaluated as to its goodness of fit. Catalog no. C7575, 2009, 656 pp., ISBN: 978-1-4200-7575-5, $79.95 / £48.99
Antedependence Models for Longitudinal Data Dale L. Zimmerman University of Iowa, Iowa City, USA
Vicente A. Núñez-Antón The University of the Basque Country (UPV/EHU), Bilbao, Spain
By gathering results scattered throughout the literature, this book offers a systematic way to learn about antedependence models and the important statistical inference procedures associated with these models. It presents informal methods of inference and formal likelihood-based methods. The authors also explore related topics and extensions, including alternative estimation methods and multivariate antedependence models. They explain how to use the methodology through illustrative examples and data sets. The relevant R functions are available for download online. Catalog no. C6426, January 2010, 288 pp., ISBN: 978-1-4200-6426-1, $89.95 / £57.99
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Statistical Theory and Methods New!
Time Series
ROC Curves for Continuous Data
Modeling, Computation, and Inference
Wojtek J. Krzanowski
Raquel Prado
University of Exeter, UK
University of California, Santa Cruz, USA
David J. Hand
Mike West
Imperial College, London, UK
Duke University, Durham, North Carolina, USA
Since ROC curves have become ubiquitous in many application areas, the various advances have been scattered across disparate articles and texts. Bringing together all the relevant material to provide a clear understanding of how to analyze ROC curves, this book first discusses the relationship between the ROC curve and numerous performance measures and then extends the theory into practice by describing how ROC curves are estimated.
Focusing on Bayesian approaches and computations using up-to-date simulation-based methods for inference, Time Series: Modeling, Computation, and Inference integrates mainstream approaches for time series modeling with significant recent developments in methodology and applications of time series analysis. It encompasses a graduate-level account of Bayesian time series modeling and analysis, a broad range of references to state-of-the-art approaches to univariate and multivariate time series analysis, and emerging topics at research frontiers. The book presents overviews of several classes of models and related methodology for inference, statistical computation for model fitting and assessment, and forecasting. The authors also explore the connections between time- and frequency-domain approaches and develop various models and analyses using Bayesian tools, such as Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) methods. They illustrate the models and methods with examples and case studies from a variety of fields, including signal processing, biomedicine, and finance. Data sets, R and MATLAB® code, and other material are available on the authors’ websites. Along with core models and methods, this text offers sophisticated tools for analyzing challenging time series problems. It also demonstrates the growth of time series analysis into new application areas.
Further building on the theory, the authors present statistical tests for ROC curves and their summary statistics. They consider the impact of covariates on ROC curves, examine the important special problem of comparing two ROC curves, and cover Bayesian methods for ROC analysis. The text then moves on to extensions of the basic analysis to cope with more complex situations, such as the combination of multiple ROC curves and problems induced by the presence of more than two classes. Focusing on design and interpretation issues, it covers missing data, verification bias, sample size determination, the design of ROC studies, and the choice of optimum threshold from the ROC curve. The final chapter explores applications that not only illustrate some of the techniques but also demonstrate the very wide applicability of these techniques across different disciplines. Catalog no. K10031, 2009, 232 pp., ISBN: 978-1-4398-0021-8, $69.95 / £42.99
Catalog no. C9336, May 2010, c. 368 pp., ISBN: 978-1-4200-9336-0, $89.95 / £57.99
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Statistical Theory and Methods Regression Modeling
New!
Applied Bayesian Hierarchical Methods
Methods, Theory, and Computation with SAS Michael Panik University of Hartford, Connecticut, USA
Peter D. Congdon
This comprehensive, accessible text provides an introduction to a diverse assortment of regression techniques using SAS to solve a wide variety of regression problems. The author fully documents the SAS programs and thoroughly explains the output produced by the programs. He explores the well-known methods of OLS and maximum likelihood regression before developing many alternative regression techniques, such as nonparametric, logistic, Bayesian, robust, fuzzy, random coefficients, spatial, polynomial, ridge, semiparametric, and more.
Emphasizing data applications, alternative modeling instructions, and computer implementation, this book provides a practical overview of methods for Bayesian analysis of models with random effects. The text focuses on applications in the health and social sciences and includes a range of worked examples in WinBUGS, BayesX, and MLWin. The author demonstrates not only the flexibility of Bayesian techniques but also the rigor that can be obtained by using Bayesian model checking techniques.
University of London, UK
Catalog no. C1972, 2009, 830 pp., ISBN: 978-1-4200-9197-7, $99.95 / £60.99
Catalog no. C7206, May 2010, c. 582 pp., ISBN: 978-1-58488-720-1, $89.95 / £57.99
Design and Analysis of Experiments
Bestseller!
Bayesian Methods for Data Analysis
Classical and Regression Approaches with SAS
Third Edition Bradley P. Carlin
Leonard C. Onyiah
University of Minnesota, Minneapolis, USA
St Cloud State University, Minnesota, USA
Thomas A. Louis Johns Hopkins Bloomberg School of Public Health, MD, USA
"… with this reorganization of chapters in the third edition, I believe that the authors have made their material more accessible to an applied audience …" —Journal of the American Statistical Association, Vol. 104, No. 486
“… particularly recommend the book to practicing biometricians who want to explore the potential for using Bayesian methods in their own work.” —Biometrics, Vol. 57, No. 3
“… the writing is excellent … the reader reaps the benefits of being in the hands of a true master …” —Journal of American Statistical Association
This modern, comprehensive text presents classical and regression approaches to experimental design and analysis. Capitalizing on the availability of cutting-edge software, the author uses both manual methods and SAS programs to carry out analyses. He provides examples to illustrate numerous designs, such as randomized complete block, Latin square, Graeco–Latin square, and balanced incomplete block designs. The text includes the full SAS code and outputs as well as end-of-chapter exercises to encourage hands-on SAS programming experience. Catalog no. C6054, 2009, 856 pp., ISBN: 978-1-4200-6054-6, $99.95 / £63.99
Catalog no. C6978, 2008, 552 pp., ISBN: 978-1-58488-697-6, $69.95 / £44.99
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Statistical Theory and Methods Bestseller!
An Introduction to Generalized Linear Models
Longitudinal Data Analysis
Third Edition
Edited by
Garrett Fitzmaurice, Marie Davidian, Geert Verbeke, and Geert Molenberghs
Annette J. Dobson University of Queensland, Herston, Australia
Adrian G. Barnett Queensland University of Technology, Kelvin Grove, Australia
"The chapters are short and concise, and the writing is clear … very worthwhile book… " —Biometrics
" … the text covers important topics that are frequently overlooked in introductory courses, such as models for ordinal outcomes. This book is an excellent resource, either as an introduction to or a reminder of the technical aspects of generalized linear models and provides a wealth of simple yet useful examples and data sets."
"… I find this book very useful for statisticians and researchers in many fields where the interest relies on studying the change of an outcome or multiple outcomes over time. … I would like to congratulate the editors and all the contributing authors for preparing this comprehensive handbook on many interesting and complementary aspects of the theory and applications of longitudinal data analysis. This handbook will have, without any doubt, an important place on the shelf of those statisticians and applied researchers working with longitudinal data." —Journal of Applied Statistics, Vo. 36, No. 10
—Journal of Biopharmaceutical Statistics, Issue 2
“… successful in filling a void in the otherwise sparse literature on the subject of generalized linear models at the introductory level … I would highly recommend this text …” —Kerrie Nelson, Statistics in Medicine, Vol. 23
Updated with Stata, R, and WinBUGS code as well as three new chapters on Bayesian analysis, this new edition of a bestseller continues to provide a cohesive framework for statistical modeling. Emphasizing numerical and graphical methods, it enables readers to understand the unifying structure that underpins GLMs. The text discusses common concepts and principles of advanced GLMs, including nominal and ordinal regression, survival analysis, and longitudinal analysis. It contains numerous examples from business, medicine, engineering, and the social sciences and offers the data sets and solutions to the exercises online.
"This is public-service broadcasting at its best. Many of the leading internationally recognized experts in the field have been assembled to write a series of expository articles on an important area of modern statistics. … Care has clearly been taken to make the book hang together—it’s not like some ‘edited tomes’ consisting of a set of papers stapled together … a must-have for anyone seriously involved with repeated measures or longitudinal data." —International Statistical Review
" … I highly recommend this book to anyone interested in learning about modern methods for longitudinal data analysis … " —Journal of Biopharmaceutical Statistics, Issue 4
Catalog no. C6587, 2009, 632 pp., ISBN: 978-1-58488-658-7, $89.95 / £57.99
Catalog no. C9500, 2008, 320 pp., Soft Cover, ISBN: 978-1-58488-950-2, $59.95 / £38.99
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Statistical Theory and Methods New! New!
Introduction to Time Series Modeling Genshiro Kitagawa Institute of Statistical Mathematics, Tokyo, Japan
With a focus on the description, modeling, prediction, and signal extraction of times series, this book provides basic tools for analyzing time series that arise in real-world problems. It employs the state-space model as a generic tool for time series modeling and presents convenient recursive filtering and smoothing methods for the statespace models. The author takes a unified approach to model evaluation based on the entropy maximization principle advocated by Hirotugu Akaike, the father of Information Criterion.
Nonparametric Statistical Inference Fifth Edition Jean Dickinson Gibbons and Subhabrata Chakraborti University of Alabama, Tuscaloosa, USA
The fifth edition of this classic text retains the flavor of the original, while providing a large collection of time-tested, commonly used nonparametric techniques. It presents in-depth coverage of the theory and methods of the most widely used nonparametric procedures in statistical analysis and offers example applications appropriate for the social, behavioral, and life sciences. This new edition is thoroughly revised and reorganized as needed, with updated examples and user-friendly tables for easy implementation.
Catalog no. C9217, April 2010, c. 296 pp., ISBN: 978-1-58488-921-2, $79.95 / £49.99
Catalog no. C7619, June 2010, c. 648 pp., ISBN: 978-1-4200-7761-2, $99.95 / £63.99
Hidden Markov Models for Time Series
New!
An Introduction Using R
Power Method Polynomials and other Transformations
Walter Zucchini University of Gottingen, Germany
Iain L. MacDonald
Statistical Simulation
Todd C. Headrick
University of Cape Town, South Africa
Southern Illinois University, Carbondale, USA
This book illustrates the wonderful flexibility of HMMs as general-purpose models for time series data. It presents an accessible overview of HMMs for analyzing time series data, from continuousvalued, circular, and multivariate series to binary data, bounded and unbounded counts, and categorical observations. It explores a variety of applications ranging from animal behavior to finance. The authors discuss how to employ R to carry out computations for parameter estimation, model selection and checking, decoding, and forecasting.
This book presents techniques for conducting a Monte Carlo simulation study, demonstrating how to use power method polynomials for simulating univariate and multivariate nonnormal distributions with specified cumulants and correlation matrices. By using the methodology and techniques developed in the text, readers can evaluate different transformations in terms of comparing percentiles, measures of central tendency, goodness-of-fit tests, and more. The book employs Mathematica® in a range of procedures and offers the source code for download online.
Catalog no. C5734, 2009, 288 pp. ISBN: 978-1-58488-573-3, $79.95 / £48.99
Catalog no. C6490, January 2010, 174 pp., ISBN: 978-1-4200-6490-2, $89.95 / £57.99
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11
Biostatistics Design and Analysis of Clinical Trials with Time-to-Event Endpoints
Missing Data in Longitudinal Studies
Karl E. Peace
Michael J. Daniels
Strategies for Bayesian Modeling and Sensitivity Analysis
Georgia Southern University, Statesboro, USA
University of Florida, Gainesville, USA
Using time-to-event analysis methodology requires careful definition of the event, censored observation, provision of adequate follow-up, number of events, and independence or "noninformativeness" of the censoring mechanisms relative to the event. Design and Analysis of Clinical Trials with Time-to-Event Endpoints provides a thorough presentation of the design, monitoring, analysis, and interpretation of clinical trials in which time-to-event is of critical interest. After reviewing time-to-event endpoint methodology, clinical trial issues, and the design and monitoring of clinical trials, the book focuses on inferential analysis methods, including parametric, semiparametric, categorical, and Bayesian methods; an alternative to the Cox model for small samples; and estimation and testing for change in hazard. It then presents descriptive and graphical methods useful in the analysis of timeto-event endpoints. The next several chapters explore a variety of clinical trials, from analgesic, antibiotic, and antiviral trials to cardiovascular and cancer prevention, prostate cancer, astrocytoma brain tumor, and chronic myelogonous leukemia trials. The book then covers areas of drug development, medical practice, and safety assessment. It concludes with the design and analysis of clinical trials of animals required by the FDA for new drug applications. Drawing on the expert contributors’ experiences working in biomedical research and clinical drug development, this comprehensive resource covers an array of time-to-event methods and explores an assortment of real-world applications. Catalog no. C6639, 2009, 616 pp., ISBN: 978-1-4200-6639-5, $99.95 / £60.99
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Joseph W. Hogan Brown University, Providence, Rhode Island, USA
"… writing is clear, precise and interesting … I have used the techniques proposed in the text with much success, teaching people the importance of separating what is observed from what is assumed. I strongly endorse this book." —Sharon-Lise Normand, Harvard School of Public Health, Boston, Massachusetts, USA
"… a well-written technical monograph … will probably have greatest appeal to statisticians with a research interest in missing data … applied biostatisticians who like to use Bayesian approaches and in particular WinBUGS will find this book very useful." —Journal of Biopharmaceutical Statistics
"…a timely and thorough review of this maturing research area. … The writing is clear and direct, the notation is sensible and consistent, and tables and figures are simple and uncluttered … Biostatisticians who seek a clear and thorough overview of the state of knowledge in this area would do well to make this excellent book their first stop." —Biometrics
With case studies on schizophrenia, aging, HIV, and smoking cessation, this book presents a unified Bayesian approach to handle missing data in longitudinal studies. The authors cover ignorable and nonignorable missingness and describe principled approaches to sensitivity analysis and the use of informative priors. They provide the WinBUGS code on a supplementary web page. Catalog no. C6099, 2008, 328 pp., ISBN: 978-1-58488-609-9, $79.95 / £49.99
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Biostatistics New!
Bayesian Missing Data Problems
Bayesian Disease Mapping
EM, Data Augmentation and Noniterative Computation
Hierarchical Modeling in Spatial Epidemiology
Ming T. Tan
Medical University of South Carolina, Charleston, USA
University of Maryland, Baltimore, USA
Guo-Liang Tian and Kai Wang Ng The University of Hong Kong, People's Republic of China
This book presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors, based on the inverse Bayes formulae. The authors focus on exact numerical solutions, a conditional sampling approach via data augmentation, and a noniterative sampling approach via EM-type algorithms. The book illustrates the methods with biostatistical models and real-world applications, including mixed effects and hierarchical models, nonresponse and contingency tables, and the constrained parameter problem reformulated as a missing data problem. Catalog no. C7749, January 2010, 344 pp., ISBN: 978-1-4200-7749-0, $89.95 / £57.99
Bayesian Methods for Measures of Agreement Lyle D. Broemeling Medical Lake, Washington, USA
"… deals with measures of agreement from a Bayesian perspective, focusing mainly on variants of Cohen’s , but also other measures included in Shoukri (2003) and von Eye and Mun (2005), frequentist texts for which this book is intended to be a Bayesian companion … uses examples throughout the book to illustrate concepts … valuable for those using the methods in Shoukri and von Eye and Mun. …" —Journal of the Royal Statistical Society, Series A, Volume 173, Issue 1
Catalog no. C3414, 2009, 340 pp., ISBN: 978-1-4200-8341-5, $89.95 / £54.99
Andrew B. Lawson
"… Lawson provides well-written reviews of many topics and many aspects of those topics are covered in his reviews. The literature cited is huge and diverse, showing the current importance of the subjects covered. One can also gain hands-on training in analysis and visual presentations …" —International Statistical Review
"… an excellent reference for intermediate learners of Bayesian disease mapping … " —J. Law, Department of Health Studies and Gerontology, University of Waterloo, Biometrics
Catalog no. C8407, 2009, 368 pp., ISBN: 978-1-58488-840-6, $79.95 / £49.99
Design and Analysis of Bioavailability and Bioequivalence Studies Third Edition Shein-Chung Chow Duke University School of Medicine, Durham, North Carolina, USA
Jen-Pei Liu National Taiwan University, Taipei
"… well written and rich in all statistical methods … provides an important reference covering nearly all of the most relevant literature …" —Journal of Biopharmaceutical Statistics
“… a thorough expose of a subject about which the authors have considerable expert knowledge. Its strengths are its encyclopedic coverage of the subject.” —Biometrics
Catalog no. C6684, 2009, 760 pp., ISBN: 978-1-58488-668-6, $99.95 / £63.99
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13
Biostatistics New!
Cluster Randomised Trials
Multiple Testing Problems in Pharmaceutical Statistics
Richard J. Hayes London School of Hygiene & Tropical Medicine, UK
Edited by
Lawrence H. Moulton
Alex Dmitrienko
Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
Eli Lilly and Company, Indianapolis, Indiana, USA
Ajit C. Tamhane Northwestern University, Evanston, Illinois, USA
Frank Bretz Novartis Pharma AG, Basel, Switzerland
This volume explores the rapidly growing area of multiple comparison research with an emphasis on pharmaceutical applications. It describes multiplicity problems encountered in pre-clinical and clinical trial settings and includes numerous case studies from actual pre-clinical experiments and clinical trials to help readers quickly learn common multiple testing methods and apply them to real-life problems. It implements the methods using SAS and R. The data sets and code are available on the book’s website.
"… a well-written book which I definitely recommend … a reference book for researchers working on the design or analysis of CRTs …" —Journal of the Royal Statistical Society, Series A, Volume 173, Issue 1
"… highly recommend this book for its unique and very important strengths … Hayes and Moulton should be congratulated for their focus on infectious diseases …" —Neil Klar, Department of Epidemiology and Biostatistics, University of Western Ontario, Journal of Biopharmaceutical Statistics, Issue 1
Catalog no. C8164, 2009, 338 pp., ISBN: 978-1-58488-816-1, $89.95 / £54.99
Catalog no. C9845, January 2010, 320 pp., ISBN: 978-1-58488-984-7, $89.95 / £57.99
Adaptive Design Theory and Implementation Using SAS and R
New!
Design and Analysis of Quality of Life Studies in Clinical Trials
Mark Chang AMAG Pharmaceuticals, Inc, Lexington, Massachusetts, USA
Second Edition Diane L. Fairclough University of Colorado Health Sciences Center, Denver, USA
Using SAS, SPSS, and R, this book addresses design and analysis aspects in enough detail so that readers can apply statistical methods to their own longitudinal studies. This edition includes a new chapter on testing models that involve moderation and mediation, a new chapter on QALYs and QTWiST specific to clinical trials, and recent methodological developments for the analysis of trials with missing data. Data sets, examples, applications, and SAS, R, and SPSS code are available on the book’s website. Catalog no. C6117, January 2010, c. 424 pp., ISBN: 978-1-4200-6117-8, $89.95 / £57.99
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"… a thorough overview of adaptive designs in clinical trials … The SAS and R programs associated with each adaptive design make the book practical as well." —Journal of the American Statistical Association, Vol. 104, No. 487
"… provides the reader with a unified and concise presentation of adaptive design theories, together with computer programs written in SAS and R for the design and simulation of adaptive trials …" —International Statistical Review
Catalog no. C962X, 2007, 440 pp., ISBN: 978-1-58488-962-5, $89.95 / £57.99
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Biostatistics
Data and Safety Monitoring Committees in Clinical Trials Jay Herson John Hopkins University, Baltimore, Maryland, USA
"This book, lively and readable and reflecting real world experiences and lessons from DMC safety monitoring, is a useful complement to other available texts on this subject." —Paul P. Gallo, Novartis Pharmaceuticals, in Journal of Biopharmaceutical Statistics, Issue 6
This book summarizes the author’s experience in serving on many DMCs and in heading up a contract research organization that provided statistical support to nearly seventy-five DMCs. It explains the difference in DMC operations between the pharmaceutical industry and NIHsponsored trials. Catalog no. C7037, 2009, 191 pp., ISBN: 978-1-4200-7037-8, $89.95 / £54.99
Sample Size Calculations in Clinical Research Second Edition Shein-Chung Chow Duke University School of Medicine, Durham, North Carolina, USA
Jun Shao University of Wisconsin, Madison, USA
Hansheng Wang Peking University, Beijing, China
"… a useful, comprehensive compendium of almost every possible sample size formula … will aid any researcher designing a study." —Biometrics
"… well written and easy to read. … a valuable reference book for biostatisticians and clinical scientists in medical or pharmaceutical research." —Statistics in Medicine
"… The main strength of the book is the vast collection of sample size calculations from many different areas of clinical research … an excellent reference …" —The Journal of Perioperative Practice
Catalog no. C9829, 2008, 480 pp., ISBN: 978-1-58488-982-3, $89.95 / £57.99
New!
Sample Sizes for Clinical Trials Steven A. Julious University of Sheffield, UK
"… comprehensive in its description of sample size calculations across a multitude of trial designs and analytical approaches … an extremely useful reference book … The nomenclature used is clear and not overly complex, and key points are highlighted both within the chapter contents as well as in tabular format at the end of each chapter. … he also covers some less common topics … " —Christopher A. Assaid, Journal of Biopharmaceutical Statistics, Issue 4
Catalog no. C7397, January 2010, 317 pp., ISBN: 978-1-58488-739-3, $79.95 / £48.99
Introduction to Statistical Methods for Clinical Trials Thomas D. Cook and David L DeMets University of Wisconsin, Madison, USA
"The (technical) statistical content is the main focus of the book and this is what helps it to stand apart from most others on clinical trials (even the more obviously statistically orientated ones) … I wholeheartedly recommend it." —Biometrics
“… The inclusion of many historically important as well as contemporary examples to illustrate various points throughout the text is a major strength, as is the inclusion of several modern topics not seen in other texts …” —Journal of Biopharmaceutical Statistics
Catalog no. C0005, 2008, 464 pp., ISBN: 978-1-58488-027-1, $73.95 / £46.99
For more information and complete contents, visit www.crcpress.com
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Biostatistics
Measurement Error
Medical Biostatistics
Models, Methods, and Applications
Second Edition
John P. Buonaccorsi
Abhaya Indrayan
University of Massachusetts, Amherst, USA
University College of Medical Science, Delhi, India
This work describes the impacts of measurement errors on naive analyses that ignore them and presents ways to correct them across a variety of statistical models, from simple one-sample problems and misclassification in categorical models to regression models, to more complex mixed and time series models. It covers correction methods based on known measurement error parameters, replication, internal or external validation data, and instrumental variables. The author includes examples using real-world data and employs SAS-IML and Stata to implement many of the techniques.
"… comprehensive introduction of basic statistical concepts and methods used in medical and health sciences … I can easily recommend this book …"
Catalog no. C6656, March 2010, c. 463 pp., ISBN: 978-1-4200-6656-2, $89.95 / £57.99
—International Statistical Review, 77, 2
"The strength of this book is the range of topics … contains adequate mathematical explanation, without going beyond the capability or interest of the intended audience …" —Marc Levine, Faculty of Pharmaceutical Sciences, University of British Colombia, Canadian Journal of Hospital Pharmacy, Vol. 61, No. 1
Catalog no. C8873, 2008, 824 pp., ISBN: 978-1-58488-887-1, $99.95 / £55.99
Translational Medicine Strategies and Statistical Methods
Bayesian Biostatistics and Diagnostic Medicine
Edited by
Dennis Cosmatos Parexel International, Rydal, Pennsylvania, USA
Lyle D. Broemeling
Shein-Chung Chow
Medical Lake, Washington, USA
Duke University School of Medicine, Durham, North Carolina, USA
"… shows how the Bayesian approach can be used to advantage … a general strength of the book is careful discussion of study designs and protocols, which is a bonus relative to many biostatistical books written from a more narrow theory and methods perspective. … A real strength is the strong integration between models and concepts on the one hand, and real studies on the other hand. The inclusion of WinBUGS code is also a plus. … highly recommended …"
This book examines the critical decisions that must be made to successfully transition from basic to clinical science. With a review of existing processes, the book presents a detailed discussion of alternative research approaches that lead to faster and more accurate decisions on data. It provides insight on biomarker development in early phase clinical trials, integrates genomic and clinical databases for the establishment of medical predictive models in various diseases, and reviews the design and analysis for translating research findings. Catalog no. C8725, 2009, 224 pp., ISBN: 978-1-58488-872-7, $89.95 / £57.99
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—Biometrics
Catalog no. C7672, 2008, 216 pp., ISBN: 978-1-58488-767-6, $83.95 / £53.99
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Computational Science New Edition of a Bestseller!
New!
A Handbook of Statistical Analyses Using R
Data Management, Statistical Analysis, and Graphics
SAS and R
Ken Kleinman
Second Edition Brian S. Everitt
Harvard Medical School, Boston, Massachusetts, USA
King's College, University of London, UK
Nicholas. J Horton
Torsten Hothorn
Smith College, Northampton, Massachusetts, USA
Ludwig-Maximilians-Universität München, Germany
"…Brian Everitt has joined forces with a recognized expert who displays an impressive command of this powerful environment … Much is to be learned in the small details that make this text interesting even for experienced users …" —Journal of Applied Statistics
"… Everitt and Hothorn have written an excellent tutorial on using R to analyze data using a wide range of standard statistical methods. … I highly recommend the text " —Joseph M. Hilbe, Journal of Statistical Software, Vol. 16
Catalog no. C7933, January 2010, 376 pp., Soft Cover, ISBN: 978-1-4200-7933-3, $54.95 / £34.99
Computational Statistics An Introduction to R
Eliminating the need to consult laborious documentation, this book presents an easy way to learn how to perform an analytical task in both SAS and R. It provides parallel examples in SAS and R to demonstrate how to use the software and derive identical answers. It also gives insight into the process of statistical coding from beginning to end by supplying worked examples of complex coding tasks. The authors offer the SAS and R data sets and code for download online. Catalog no. C7057, January 2010, 343 pp., ISBN: 978-1-4200-7057-6, $69.95 / £44.99
Interactive Graphics for Data Analysis Principles and Examples Martin Theus Munich, Germany
Günther Sawitzki StatLab, Heidelberg, Germany
"… a fresh perspective on teaching statistics … introduces its topics and the corresponding methodologies well … is well put together and quite enjoyable …" —Journal of Statistical Software
"… a well-written and nicely organized … it is the integration of interesting examples and associated R code that make the text a pleasure to read and work through. … will be most useful to computer savvy readers …" —Ronald D. Fricker, Jr., The American Statistician
Catalog no. C6782, 2009, 264 pp., ISBN: 978-1-4200-8678-2, $79.95 / £48.99
Simon Urbanek Madison, New Jersey, USA
"… gives you the ideas and tools to visualize, explore, and understand all your data … also introduces Mondrian, a powerful, easy-to-use tool that allows you to generate and explore everything shown. … If you have any data to present (or to mark), whether you are a psychologist, physicist, geographer, biologist or historian, whether writing a paper or dissertation, use this book … You have no excuse not to use it." —Times Higher Education
Catalog no. C5947, 2009, 290 pp., ISBN: 978-1-58488-594-8, $79.95 / £39.99
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17
Computational Science Introduction to Scientific Programming and Simulation Using R
Bestseller!
Statistical Computing with R
Owen Jones, Robert Maillardet, and Andrew Robinson
Maria L. Rizzo Bowling Green State University, Ohio, USA
University of Melbourne, Parkville, Australia
"… an excellent introduction to scientific programming with R … clear prose, logical structure, well-documented code and realistic examples make the book a pleasure to read … I would strongly recommend this book for readers interested in using R for simulations, particularly for those new to scientific programming or R." —Significance
"… The writing style is easy to read … If you have never read a book on scientific programming and simulation, then I recommend that you start with this one." —International Statistical Review
"… an excellent tutorial on the R language, providing examples that illustrate programming concepts in the context of practical computational problems … " —Tzvetan Semerdjiev, in Zentralblatt Math, Vol. 1137
This text covers the traditional core material of computational statistics, with an emphasis on using the R language via an examples-based approach. It illustrates every algorithm with at least one fully implemented example coded in R and offers the source code for all examples online. Catalog no. C5459, 2008, 416 pp., ISBN: 978-1-58488-545-0, $83.95 / £39.99
Catalog no. C6872, 2009, 472 pp., ISBN: 978-1-4200-6872-6, $79.95 / £48.99
A Handbook of Statistical Analyses using SAS
New!
Graphics for Statistics and Data Analysis with R
Third Edition
Kevin J. Keen
Geoff Der
University of Northern British Columbia, Prince George, Canada
University of Glasgow, Scotland
Brian S. Everitt
This text presents the basic principles of graphical design as applied to the presentation of data as well as a wide range of graphical displays for data presentation. Chapters are arranged to correspond with progressive learning, beginning with univariate statistical methods, analysis of contingency tables, linear regression models, and multivariate methods for data analysis. The R scripts for all of the figures in the text are available for download on the book’s website. Catalog no. C0756, April 2010, c. 480 pp., ISBN: 978-1-58488-087-5, $69.95 / £39.99
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King's College, University of London, UK
"… They cover a wide range of topics efficiently—the explanations are brief, but not overly simplistic; the examples are sufficient and never excessive. … this a good resource for the user who is acquainted with the very basics of SAS, but unsure of how to conduct analysis. …" —Journal of Statistical Software
"… combines data management using the SAS system and data analysis into one book. … a great reference …" —Clinical Trials
Catalog no. C7842, 2009, 392 pp., Soft Cover, ISBN: 978-1-58488-784-3, $54.95 / £34.99
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Computational Science
An Introduction to Stata Programming
Introduction to Data Technologies
Christopher F. Baum
Paul Murrell
Boston College, Chestnut Hill, Massachusetts, USA
The University of Auckland, New Zealand
This work focuses on three types of Stata programming: do-file programming, ado-file programming, and Mata functions that work in conjunction with do- and ado-files. It explains how to usefully automate work with Stata and how to use Stata more effectively through programming on one or more of these levels. The text follows a unique format by offering "cookbook" chapters after each main chapter. These cookbook chapters look at how to perform a specific programming task with Stata and provide a complete solution to the problem.
Written by a member of the R Development Core Team, this resource provides important information on how to work with research data. It contains a collection of diverse, computer-related topics, connecting them through numerous, realworld case studies. The author describes open source technologies and open standards and devotes separate chapters to each computer language, including HTML, XML, SQL, and R. In addition, the author’s website includes a suite of exercises as well as the code and data sets used in the case studies.
Catalog no. N10106, 2009, 362 pp., Soft Cover, ISBN: 978-1-59718-045-0, $69.95 / £44.99
Catalog no. C6517, 2009, 418 pp., ISBN: 978-1-4200-6517-6, $69.95 / £42.99
Bestseller!
Computational Statistics Handbook with MATLAB®
Meta-Analysis An Updated Collection from the Stata Journal
Second Edition Wendy L. Martinez The Department of Defense, Fredericksburg, Virginia, USA
Jonathan Sterne
Angel R. Martinez Strayer University, Fredericksburg, Virginia, USA
"… useful as a reference where one can look to get a concise description of a statistical methodology and MATLAB code that can be used to implement it … the book is excellent." – Michael J. Evans, in Mathematical Reviews
"… a valuable reference to practicing statisticians (or statistical researchers) using MATLAB as their computing engines." —Biometrics
“As a long-time user of MATLAB, I find this book useful as a reference, and thus recommend it highly” —Journal of the American Statistical Association, Vol. 99, No. 466
Catalog no. C5661, 2008, 792 pp., ISBN: 978-1-58488-566-5, $89.95 / £39.99
This collection provides detailed descriptions of meta-analytic methods and their implementation in Stata. It delineates the statistical methods behind the rapid increase in the number of metaanalyses reported in the social science and medical literature. The book shows how to conduct and interpret meta-analyses and how to produce highly flexible graphical displays. Using metaregression, it examines reasons for between-study variability in effect estimates. The book also employs advanced methods for the meta-analysis of diagnostic test accuracy studies, dose-response meta-analysis, meta-analysis with missing data, and multivariate meta-analysis. Catalog no. N10105, 2009, 259 pp., Soft Cover, ISBN: 978-1-59718-049-8, $49.95 / £31.99
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Data Mining and Machine Learning Constrained Clustering
New!
Relational Data Clustering
Advances in Algorithms, Theory, and Applications
Models, Algorithms, and Applications
Edited by
Bo Long
Sugato Basu
Yahoo! Labs, Sunnyvale, California, USA
Google, Inc. Mountain View, California, USA
Zhongfei Zhang
Ian Davidson
State University of New York, Binghamton, USA
University of California, Davis, USA
Philip S. Yu
Kiri Wagstaff Jet Propulsion Laboratory, Pasadena, California, USA
From the Foreword “… this book shows how constrained clustering can be used to tackle large problems involving textual, relational, and even video data. After reading this book, you will have the tools to be a better analyst [and] to gain more insight from your data, whether it be textual, audio, video, relational, genomic, or anything else.” —Dr. Peter Norvig, Director of Research, Google, Inc., Mountain View, California, USA
Catalog no. C9969, 2009, 472 pp., ISBN: 978-1-58488-996-0, $79.95 / £49.99
This book reflects the recent emergence of relational data clustering as an important sub-specialty of data clustering, with applications in text mining, social network analysis, collaborative filtering, and bioinformatics. It presents an indepth, systematic discussion of the models, algorithms, and applications for relational data clustering. The book also covers recently emerging models in relational data clustering, including graph-based models, matrix factorization-based models, and probabilistic models. Catalog no. C7261, May 2010, c. 216 pp., ISBN: 978-1-4200-7261-7, $79.95 / £49.99
The Top Ten Algorithms in Data Mining
Next Generation of Data Mining
Edited by
Edited by
Xindong Wu
Hillol Kargupta, Jiawei Han, Philip S. Yu, Rajeev Motwani, and Vipin Kumar
University of Vermont, Burlington, USA
Vipin Kumar
Focusing on the future of data mining, this volume addresses a variety of emerging data mining challenges and potential solutions. It shows how innovative data mining tools and techniques can be applied in a range of areas, including e-science, engineering, social science, ecology, finance, and medicine. With contributions from many well-respected researchers and practitioners in the community, the book examines the algorithms, middleware, infrastructure, and privacy policies associated with ubiquitous, distributed, and high performance data mining. Catalog no. C5867, 2009, 601 pp., ISBN: 978-1-4200-8586-0, $89.95 / £57.99
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University of Illinois, Chicago, USA
University of Minnesota, Minneapolis, USA
Identifying some of the most influential, widely used algorithms, this volume provides a description of each algorithm, discusses the impact of the algorithms, and reviews current and future research on the algorithms. Each chapter focuses on a particular algorithm and is written by either the original authors of the algorithm or worldclass researchers who have extensively studied the respective algorithm. The book concentrates on the following important algorithms: C4.5, kMeans, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. Catalog no. C9641, 2009, 232 pp., ISBN: 978-1-4200-8964-6, $79.95 / £48.99
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Data Mining and Machine Learning New! New!
Temporal Data Mining Theophano Mitsa
Handbook of Natural Language Processing Second Edition
Software Consultant, Melrose, Massachusetts, USA
Edited by
"… a valuable reference for both the novice and the established practitioner. The clear, concise and instructive style will make this book particularly attractive to graduate students, researchers and industry professionals."
University of New South Wales, Sydney, Australia
—Dr. Wasim Q. Malik, Massachusetts Institute of Technology and Harvard Medical School, Cambridge, USA
"… a valuable overview … provides the reader with the tools to dig deeper into topics of interest." —Dr. Brian Tracey, Signal Processing Project Leader at Neurometrix, Inc.
Catalog no. C9765, March 2010, 395 pp., ISBN: 978-1-4200-8976-9, $79.95 / £49.99
Text Mining Classification, Clustering, and Applications
Nitin Indurkhya
Fred J. Damerau Goshen, Connecticut, USA
This comprehensive handbook presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition offers greater prominence to statistical approaches and a broader multilingual scope to include Asian and European languages. It also contains a new applications section that covers many wellknown and emerging applications, including machine translation, biomedical text mining, and sentiment analysis. In addition, an actively maintained companion wiki provides online resources, supplementary information, and up-to-date developments. Catalog no. C5921, February 2010, 704 pp., ISBN: 978-1-4200-8592-1, $99.95 / £63.99
Edited by
Ashok Srivastava Ames Research Center, Moffett Field, California, USA
Mehran Sahami Stanford University, California, USA
"… a worthy contribution to the field of text mining … brings unity and clarity to a disjointed and sometimes perplexing field and serve as the perfect introduction …" —Peter Norvig, Director of Research, Google, Inc., Mountain View, California, USA
"… a state-of-the-art, outstanding collection of overviews on text mining by a group of leading researchers in the field. The book meets an imminent need for an up-to-date overview of this exciting, dynamic research frontier …" —Jiawei Han, University of Illinois at UrbanaChampaign, USA
Catalog no. C5940, 2009, 328 pp., ISBN: 978-1-4200-5940-3, $79.95 / £48.99
Machine Learning An Algorithmic Perspective Stephen Marsland Massey University, Palmerston North, New Zealand
"If you are interested in learning enough AI to understand the sort of new techniques being introduced into Web 2 applications, then this is a good place to start … covers the subject matter of many an introductory course on AI and it has references to the source material and further reading but it is written in a fairly casual style … much of the mathematics is explained in ways that make it fairly clear what is going on …" —I-Programmer
Catalog no. C6718, 2009, 406 pp., ISBN: 978-1-4200-6718-7, $69.95 / £42.99
For more information and complete contents, visit www.crcpress.com
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Statistics for Psychology, Social Science, and Law New!
New!
Multivariable Modeling and Multivariate Analysis for the Behavioral Sciences
Applied Survey Data Analysis Steve G. Heeringa, Brady West, and Patricia A. Berglund University of Michigan, Ann Arbor, USA
Brian S. Everitt King's College, University of London, UK
With many real-world examples, graphs, and exercises, this text presents an accessible introduction to intermediate statistical methods for behavioral scientists. It contains a large number of real data sets arising from actual problems, including cognitive behavioral therapy, crime rates, and drug usage. Assuming some familiarity with introductory statistics, the author separates mathematical details from the main body of the text and removes the burden of performing necessary calculations by encouraging the use of R and providing the code online. Catalog no. K10396, January 2010, 320 pp., Soft Cover, ISBN: 978-1-4398-0769-9, $69.95 / £29.99
Analysis of Multivariate Social Science Data
Catalog no. C8066, May 2010, c. 462 pp., ISBN: 978-1-4200-8066-7, $79.95 / £49.99
Bayesian Methods A Social and Behavioral Sciences Approach, Second Edition
Second Edition David J. Bartholomew, Fiona Steele, Jane Galbraith, and Irini Moustaki
Jeff Gill Washington University, St. Louis, Missouri, USA
"… Written by some of the leaders in the field, the second edition expands the horizon of the first edition by three new chapters … Good examples abound [and] … so do worked-out applications. … I also like the authors’ effort to compare related methods across the chapters … The website is a treasure trove … the book is essential …" —Tim Futing Liao, University of Illinois, Journal of the Royal Statistical Society (Series A)
Catalog no. C9608, 2008, 384 pp., Soft Cover, ISBN: 978-1-58488-960-1, $69.95 / £29.99
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With many examples and exercises based on major real-world survey data sets, this book provides a statistical overview of the analysis of complex sample survey data. It presents methods and models for survey data analysis, including the linear regression, generalized linear, Cox proportional hazards, and discrete time models. It also explores new developments in advanced statistical techniques. The authors show how design characteristics are easily incorporated into the statistical methods and software for survey estimation and inference.
"… will be very useful for a well-motivated reader … a very readable book, based on solid scholarship and written with conviction, gusto, and a sense of fun." —International Statistical Review, 77, 2
"… a brilliant and importantly very accessible introduction to the concept … The clear strength of the book is in making the concept practical and accessible, without necessarily dumbing it down. … The coverage is also remarkable." —Dr. S.V. Subramanian, Harvard School of Public Health, Cambridge, Massachusetts, USA
Catalog no. C5629, 2008, 752 pp., ISBN: 978-1-58488-562-7, $73.95 / £46.99
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Statistics for Psychology, Social Science, and Law New!
Forthcoming!
Foundations of Factor Analysis
Choice-Based Conjoint Analysis
Second Edition
Models and Designs
Stanley A Mulaik
Damaraju Raghavarao, James B. Wiley, and Pallavi Chitturi
Georgia Institute of Technology, School of Psychology, Atlanta, USA
Providing a practical, thorough understanding of how factor analysis works, this text discusses the assumptions underlying the equations and procedures of this method. This long-awaited second edition includes a new chapter on the multivariate normal distribution, its general properties, and the concept of maximum-likelihood estimation. It also contains a rewritten chapter on analytic oblique rotation that focuses on the gradient projection algorithm and its applications as well as a revised chapter on confirmatory factor analysis. Catalog no. K10005, January 2010, 548 pp., ISBN: 978-1-4200-9961-4, $79.95 / £39.99
Linear Causal Modeling with Structural Equations Stanley A. Mulaik
Temple University, Philadelphia, Pennsylvania, USA
Disseminating information from researchers in various fields, this compilation presents the research themes, methods, and findings, making it a significant reference for design researchers and design practitioners interested in furthering understanding of design activity in real-world settings. It presents an analysis of digital video recordings of a series of design meetings on the conceptual stages of a design project. The data was gathered from design meetings taking place as part of naturally occurring design practice, rather than being gathered through a staged experiment in which the conditions are highly controlled. Catalog no. K10020, August 2010, c. 168 pp., ISBN: 978-1-4200-9996-6, $89.95 / £57.99
Microeconometrics Using Stata A. Colin Cameron University of California, Davis, USA
Pravin K. Trivedi
Georgia Institute of Technology
Indiana University, Bloomington, USA
Emphasizing causation as a functional relationship between variables, this book covers the basics of SEM. The author discusses the history and philosophy of causality and its place in science and presents graph theory as a tool for the design and analysis of causal models. He explains how the algorithms in SEM are derived and how they work, covers various indices and tests for evaluating the fit of structural equation models to data, and explores recent research in graph theory, path tracing rules, and model evaluation.
An outstanding introduction to microeconometrics and how to do microeconometric research using Stata, this book covers topics often left out of microeconometrics textbooks and omitted from basic introductions to Stata. The authors introduce simulation methods and then use them to illustrate features of the estimators and tests described in the rest of the book. They demonstrate how to use Stata’s programming features to implement methods for which Stata does not have a specific command.
Catalog no. K10039, 2009, 468 pp., ISBN: 978-1-4398-0038-6, $79.95 / £48.99
Catalog no. N10070, 2009, 692 pp., Soft Cover, ISBN: 978-1-59718-048-1, $74.95 / £49.99
For more information and complete contents, visit www.crcpress.com
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Environmental and Ecological Statistics New!
Bayesian Analysis for Population Ecology
New!
Ruth King, Byron J.T. Morgan, Olivier Gimenez, and Stephen P. Brooks
Song S. Qian
Environmental and Ecological Statistics with R Nicholas School of the Environment, Duke University, Durham, North Carolina, USA
Emphasizing model choice and model averaging, this book presents Bayesian methods for analyzing complex ecological data. It provides a basic introduction to Bayesian methods that assumes no prior knowledge. The book includes detailed descriptions of methods that deal with covariate data and covers techniques at the forefront of research, such as model discrimination and model averaging. Leaders in the statistical ecology field, the authors apply the theory to a wide range of actual case studies and illustrate the methods using WinBUGS and R.
Emphasizing the inductive nature of statistical thinking, this text connects applied statistics to the environmental and ecological fields. It follows the general approach to solving a statistical modeling problem, covering model specification, parameter estimation, and model evaluation. The text explains how to conduct data analysis, discusses simulation for model checking, and presents multilevel regression models. The author uses many examples to illustrate the statistical models and presents R implementations of the models. The data sets and R scripts used in the book are available online.
Catalog no. K10597, January 2010, 456 pp., ISBN: 978-1-4398-1187-0, $79.95 / £49.99
Catalog no. C6206, January 2010, 440 pp., Soft Cover, ISBN: 978-1-4200-6206-9, $79.95 / £49.99
Statistics for Environmental Science and Management
Statistical Detection and Surveillance of Geographic Clusters
Second Edition
Peter Rogerson
Bryan F.J. Manly
University of Buffalo, New York, USA
Western EcoSystem Technology, Inc., Laramie, Wyoming, USA
Ikuho Yamada
Using a nonmathematical approach, this second edition of a bestseller introduces frequently used statistical methods and practical applications for the environmental field. The book features updated references and examples along with new and expanded material on data quality objectives, the generalized linear model, spatial data analysis, and Monte Carlo risk assessment. Additional topics covered include environmental monitoring, impact assessment, censored data, environmental sampling, the role of statistics in environmental science, assessing site reclamation, and drawing conclusions from data. Catalog no. C6147, 2009, 292 pp., ISBN: 978-1-4200-6147-5, $69.95 / £44.99
University of Utah, Salt Lake City, USA
"… a comprehensive presentation that will provide a valuable reference source for years to come. I recommend that anyone working with geographic information systems (GIS) consults this volume, as there are many valuable nuggets of information—many unexpected!" —International Statistical Review
A thorough review of methods for cluster detection, this book is organized according to the different types of hypotheses that can be investigated using these techniques. The authors also discuss the surveillance of geographic patterns and describe applications using GeoSurveillance software. Catalog no. C9357, 2009, 324 pp., ISBN: 978-1-58488-935-9, $89.95 / £57.99
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Statistical Genetics and Bioinformatics New!
New!
Microarray Image Analysis
Gene Expression Studies Using Affymetrix Microarrays
An Algorithmic Approach Karl Fraser, Zidong Wang, and Xiaohu Liu Brunel University, Uxbridge, UK
This book presents an automatic system for microarray image processing to make decoupling a reality. The proposed system integrates and extends traditional analytical-based methods and custom-designed novel algorithms. The book first explores a new technique that takes advantage of a multiview approach to image analysis and addresses the challenges of applying powerful traditional techniques, such as clustering, to full-scale microarray experiments. It then presents an effective feature identification approach, an innovative technique that renders highly detailed surface models, a new approach to subgrid detection, a novel technique for the background removal process, and a useful technique for removing "noise." The authors also develop an expectation–maximization (EM) algorithm for modeling gene regulatory networks from gene expression time series data. The final chapter describes the overall benefits of these techniques in the biological and computer sciences and reviews future research topics. This book systematically brings together the fields of image processing, data analysis, and molecular biology to advance the state of the art in this important area. Although the text focuses on improving the processes involved in the analysis of microarray image data, the methods discussed can be applied to a broad range of medical and computer vision analysis areas. Catalog no. C9153, January 2010, 335 pp., ISBN: 978-1-4200-9153-3, $89.95 / £57.99
Hinrich Gohlmann and Willem Talloen Johnson & Johnson, Beerse, Belgium
The Affymetrix GeneChip® system is one of the most widely adapted microarray platforms. However, due to the overwhelming amount of information available, many Affymetrix users tend to stick to the default analysis settings and may end up drawing sub-optimal conclusions. Written by a molecular biologist and a biostatistician with a decade of experience between them, Gene Expression Studies Using Affymetrix Microarrays tears down the omnipresent language barriers among molecular biology, bioinformatics, and biostatistics by explaining the entire process of a gene expression study from conception to conclusion. This authoritative resource covers important technical and statistical pitfalls and problems, helping not only to explain concepts outside the domain of researchers, but to provide additional guidance in their field of expertise. The book also describes technical and statistical methods conceptually with illustrative, full-color examples, enabling those inexperienced with gene expression studies to grasp the basic principles. The book provides novices with a detailed, yet focused introductory course and practical user guide. Specialized experts will also find it useful as a translation dictionary to understand other involved disciplines or to get a broader picture of microarray gene expression studies in general. Although focusing on Affymetrix gene expression, this globally relevant guide covers topics that are equally useful for other microarray platforms and other Affymetrix applications. Catalog no. C6515, January 2010, 359 pp., ISBN: 978-1-4200-6515-2, $89.95 / £54.99
For more information and complete contents, visit www.crcpress.com
25
Statistical Genetics and Bioinformatics
Bayesian Modeling in Bioinformatics
Introduction to Machine Learning and Bioinformatics
Edited by
Sushmita Mitra
Dipak K. Dey
Indian Statistical Institute, Kolkata, India
New!
University of Connecticut, Storrs, USA
Sujay Datta SCHARP, Seattle, Washington, USA
Samiran Ghosh Indiana University-Purdue University, Indianapolis, USA
Theodore Perkins McGill Centre for Bioinformatics, Montreal, Quebec, Canada
Bani K. Mallick
George Michailidis
Texas A&M University, College Station, USA
University of Michigan, Ann Arbor, USA
This volume discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research, such as cancer. It presents a broad overview of statistical inference, clustering, and classification problems in two main high-throughput platforms: microarray gene expression and phylogenic analysis. Illustrating concepts using realworld data, the book covers a variety of recently developed Bayesian techniques, along with applications in genome-wide studies, phylogenetics, breast cancer, expression genomics, and more.
"… One of the strengths of this book is the clear notation with a mathematical and statistical flavor … very readable for a variety of interested learners, researchers, and audiences from various backgrounds and disciplines. …"
Catalog no. C7017, April 2010, c. 536 pp., ISBN: 978-1-4200-7017-0, $89.95 / £57.99
—Biometrics
"… a well-structured book that is a good starting point for machine learning in bioinformatics … Using many popular examples, the statistical theory becomes comprehensible and bioinformatics examples motivate [readers] to apply the concepts to real data." —Markus Schmidberger, Journal of Statistical Software
Catalog no. C682X, 2008, 384 pp., ISBN: 978-1-58488-682-2, $79.95 / £39.99
R Programming for Bioinformatics
Statistics in Human Genetics and Molecular Biology
Robert Gentleman
Cavan Reilly
Bestseller!
"This is a very excellent book. … I think this is actually the best handbook on R programming that is currently available. … an indispensable handbook for R programmers …" —Journal of Statistical Software
This practical guide focuses on the programming skills needed to use R for the solution of bioinformatics and computational biology problems. It also discusses the interfacing of R with other languages and explains how to write software packages as well as debug and profile R code. Catalog no. C6367, 2009, 328 pp., ISBN: 978-1-4200-6367-7, $69.95 / £44.99
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University of Minnesota, Minneapolis, USA
Focusing on the roles of different segments of DNA, this book provides a basic understanding of problems arising in the analysis of genetics and genomics. It presents statistical applications in genetic mapping, DNA/protein sequence alignment, and analyses of gene expression data from microarray experiments. The text covers basic molecular biology, likelihood-based statistics, physical mapping, markers, linkage analysis, parametric and nonparametric linkage, sequence alignment, feature recognition, hidden Markov models, and Bayesian approaches. Catalog no. C7263, 2009, 280 pp., ISBN: 978-1-4200-7263-1, $59.95 / £38.99
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Statistical Genetics and Bioinformatics DNA Methylation Microarrays
New!
Meta-analysis and Combining Information in Genetics and Genomics
Experimental Design and Statistical Analysis Sun-Chong Wang
Rudy Guerra
National Central University, Chungli Taoyuan, Taiwan
Rice University, Houston, Texas, USA
Art Petronis Centre for Addiction and Mental Health, Toronto, Ontario, Canada
"… a helpful guide for researchers and students with an interest in performing genomic studies using high-throughput microarrays. … A wide range of useful data analysis tools are covered … Other strengths throughout the book include the discussion of experimental design, the mention of software for certain analyses, and the inclusion of more advanced methods such as wavelets and genetic algorithms. … Overall, this book gives a nice summary of methods used for the analysis of hybridization-based microarray data. …" —Biometrics
Catalog no. C6727, 2008, 256 pp., ISBN: 978-1-4200-6727-9, $79.95 / £49.99
Handbook of Hidden Markov Models in Bioinformatics
Darlene R. Goldstein EPFL SB IMA STAT, Switzerland
This book provides novel techniques for analyzing data from modern biological studies that involve multiple data sets, either of the same type or multiple data sources. It addresses the combination of similar data types: genotype data from genomewide linkage scans and data derived from microarray gene expression experiments. The contributors show how some data combination problems can arise even within the same basic framework and offer solutions to these problems. They also discuss the combined analysis of different data types. Catalog no. C522X, January 2010, 360 pp., ISBN: 978-1-58488-522-1, $99.95 / £63.99
Statistical and Computational Pharmacogenomics Rongling Wu University of Florida, Gainesville, USA
Martin Gollery
Min Lin
Tahoe Informatics, Incline Village, Nevada, USA
Duke Clinical Research Institute, Durham, North Carolina, USA
This handbook focuses on how to choose and use various methods and programs available for HMMs. It explores HMM implementations in bioinformatics, including SAM, HMMER, Wise2, PSIBLAST, and Meta-MEME, and shows how databases and programs, such as Pfam, SMART, SUPERFAMILY, and PANTHER are used in bioinformatics projects. The book discusses the use of HMMs for discovering the homology of a protein family, explains how to build custom HMM databases, and offers solutions to help overcome slow searches. It includes a CD-ROM of related material.
"… recommended to both statisticians and life scientists … gives the scientist a better understanding of what the analysis is doing and why it is needed."
Catalog no. C6846, 2008, 176 pp., ISBN: 978-1-58488-684-6, $59.95 / £38.99
Catalog no. C8288, 2009, 368 pp., ISBN: 978-1-58488-828-4, $79.95 / £49.99
—John A. Wass, Ph.D., Scientific Computing
This book presents recent developments in statistical methodology with a number of detailed worked examples that outline how these methods can be applied. It provides background on genetics and modeling and presents the tools needed to understand and model the genetic variation for drug response.
For more information and complete contents, visit www.crcpress.com
27
Statistics for Business, Finance, and Economics Introduction to Spatial Econometrics
New!
McCoy College of Business Administration, San Marcos, Texas,
Monte Carlo Methods and Models in Finance and Insurance
R. Kelley Pace
Ralf Korn
Louisiana State University, Baton Rouge, USA
University of Kaiserslautern, Germany
"… the right balance of theoretical detail and applied illustrations of the methods discussed … The authors’ topic is an exciting area of statistics which will clearly evolve further and develop in the coming years"
Elke Korn
James LeSage
—International Statistical Review
"The research community needs a text like this … will become a standard reference in the field and will find a welcome home on the shelf of every empirical researcher interested in spatial econometric techniques." —Donald Lacombe, Ohio University, Athens, USA
Catalog no. C6424, 2009, 374 pp., ISBN: 978-1-4200-6424-7, $89.95 / £54.99
Quantitative Fund Management
Independent Mathematical Consultant, Stelzenberg, Germany
Gerald Kroisandt Fraunhofer ITWM, Kaiserslautern, Germany
This book incorporates the application background of finance and insurance with the theory and applications of Monte Carlo methods. It presents methods and algorithms, including the multilevel Monte Carlo method, the statistical Romberg method, and the Heath–Platen estimator, as well as recent financial and actuarial models, such as the Cheyette and dynamic mortality models. The book enables readers to find the right algorithm for a desired application and illustrates complicated methods and algorithms with simple applications to provide an easy understanding of key properties. Catalog no. C7618, March 2010, 484 pp., ISBN: 978-1-4200-7618-9, $89.95 / £57.99
New!
Edited by
Gautam Mitra
Applied Statistics for Business and Economics
Brunel University, Uxbridge, UK
Robert M. Leekley
Georg Pflug
Illinois Wesleyan University, Bloomington, USA
M.A.H. Dempster University of Cambridge and Cambridge Systems Associates Limited, UK
Department of Statistics, 8 Decision Systems, University of Vienna, Austria
"… likely to become a cherished reference … its emphasis on dynamic solutions to portfolio decision problems brings vastly more realism than prior models that implied investor behavior that was static and unresponsive to changes in market conditions and investor financial circumstances…" —Dan diBartelomeo, President, Northfield Information Services, Boston, Massachusetts, USA
Catalog no. C1918, 2009, 486 pp., ISBN: 978-1-4200-8191-6, $79.95 / £49.99
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Designed for a one-semester course, this text offers students in business and the social sciences an effective introduction to some of the most basic and powerful techniques available for understanding their world. To help with the examples, the author offers both actual and hypothetical databases on his website. He enables readers to summarize data in insightful ways using charts, graphs, and summary statistics and shows how to make inferences from samples, especially about relationships. Catalog no. K10296, April 2010, c. 496 pp., ISBN: 978-1-4398-0568-8, $79.95 / £49.99
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Statistics for Business, Finance, and Economics
Interest Rate Modeling Theory and Practice Lixin Wu University of Science & Technology, Kowloon, Hong Kong
New!
Stochastic Financial Models Douglas Kennedy Trinity College, Cambridge, UK
This text portrays the theory of interest rate modeling as a three-dimensional object of finance, mathematics, and computation. It introduces all models with financial-economical justifications, develops options along the Martingale approach, and handles option evaluations with precise numerical methods. Using a top-down method, the author shows readers how to build and use models. The text includes exercises and realworld examples, along with code, tables, and figures accessible on the author’s website. A solutions manual is available for qualifying instructors.
This text provides a hands-on, sound introduction to mathematical finance. Assuming no prior knowledge of stochastic calculus or measure-theoretic probability, the author includes the relevant mathematical background as well as many exercises with solutions. He first presents the classical topics of utility and the mean-variance approach to portfolio choice. Focusing on derivative pricing, the text then covers the binomial model, the general discrete-time model, Brownian motion, the Black–Scholes model and various interest-rate models.
Catalog no. C0569, 2009, 353 pp., ISBN: 978-1-4200-9056-7, $79.95 / £48.99
Catalog no. C3452, January 2010, 264 pp., ISBN: 978-1-4200-9345-2, $69.95 / £44.99
New!
Stochastic Dominance and Applications to Finance, Risk and Economics Songsak Sriboonchita, Wing-Keung Wong, Sompong Dhompongsa, and Hung T. Nguyen This accessible guide helps readers build a useful repertoire of mathematical tools in decision making under uncertainty, especially in investment science. Using real data and statistical procedures, the book introduces utility theory for decision making under risk and discusses various research issues, such as how to use empirical data to arrive at decisions and how to conduct statistical tests when the data is coarse. It also explores numerous applications, including financial diversification, evaluating hedge funds, and income inequality. Catalog no. C8266, January 2010, 455 pp., ISBN: 978-1-4200-8266-1, $89.95 / £57.99
Forthcoming!
Stochastic Finance A Numeraire Approach Jan Vecer Columbia University , New York, New York, USA
This text presents a novel approach to pricing derivatives contracts using numeraire techniques. Focusing on fundamental finance principles instead of mathematical theory, the author considers the price of an asset as an exchange ratio between goods that pay for each other, rather than expressing prices in currency terms. This approach leads to simple derivations of pricing formulas that are model independent. With illustrative examples and key solutions, the text emphasizes that no agent in the economy is able to produce a risk-free profit. Catalog no. K10632, July 2010, c. 256 pp., ISBN: 978-1-4398-1250-1, $69.95 / £44.99
For more information and complete contents, visit www.crcpress.com
29
Statistics for Engineering, Reliability, and Quality Control Analytical Methods for Risk Management
The Weibull Distribution
A Systems Engineering Perspective
A Handbook Horst Rinne
Paul R. Garvey
University of Giessen
The MITRE Corporation, Bedford, Massachusetts, USA
This book describes the foundation processes and analytical practices for identifying, analyzing, measuring, and managing risk in traditional systems, systems-of-systems, and enterprise systems. The author presents a new way, in the form of a supplier–provider framework, to model and measure risk in the engineering of enterprise systems being developed by capabilities-based approaches. He also explores research ideas for the development of advanced risk analysis and management protocols and discusses success factors for managing risk in the engineering of systems. Catalog no. C6374, 2009, 288 pp., ISBN: 978-1-58488-637-2, $99.95 / £63.99
Acceptance Sampling in Quality Control
Catalog no. C7436, 2009, 808 pp., ISBN: 978-1-4200-8743-7, $99.95 / £63.99
New!
Modeling and Analysis of Stochastic Systems
Second Edition Edward G. Schilling Rochester Institute of Technology, New York, USA
Second Edition Vidyadhar G. Kulkarni
Dean V. Neubauer
University of North Carolina, Chapel Hill, USA
Corning Incorporated, Horseheads, New York, USA
"… Like the first edition, this one remains a comprehensive one and includes a few new topics … continues to be equally useful … I think it will be a nice addition to your personal library!" —Technometrics, Vol. 51, No. 3
"… a classic, and is considered by many as a ‘must-have book’ … a comprehensive collection of acceptance sampling methods and is an excellent mix of theory and application …" —Journal of Quality Technology, Vol. 41, No. 4
Catalog no. C9527, 2009, 700 pp., ISBN: 978-1-58488-952-6, $119.95 / £72.99
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Compiling findings from many scientific journals and research papers, this handbook focuses on the origin, statistical properties, and related distributions of the Weibull distribution. It also presents various approaches to estimate the parameters of this distribution under all possible situations of sampling data as well as approaches to parameter and goodness-of-fit testing. The author provides illustrative examples from the biological, environmental, health, physical, and social sciences and lists several statistical software packages capable of performing Weibull analysis.
"… Plenty of applications, examples, and exercises bring the reader to the intuitive understanding of the subject." —Zentralblatt MATH
This text covers the most important classes of stochastic processes used in the modeling of diverse systems. Along with new appendices that collect results from analysis and differential and difference equations, this edition contains a new chapter on diffusion processes with applications to finance. MATLAB®-based programs can be downloaded from the author’s website. Catalog no. K10430, January 2010, 563 pp., ISBN: 978-1-4398-0875-7, $99.95 / £63.99
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NEW!
Collecting the works of prominent researchers, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area. Deftly balancing theory and application, this book: u Provides broad, thorough coverage of this vibrant area, from historical to contemporary topics u Focuses on continuous and discrete spatial variation, spatial point patterns, and spatio-temporal processes u Presents the theory and applications with real-world data examples u Explores the modeling advances, computational approaches, and new methodology that have emerged in recent years u Covers multivariate spatial process models, spatial aggregation, spatial misalignment, and spatial gradients in depth u Draws on contributions from highly regarded international experts
Catalog no. C7287, March 2010, 608 pp., ISBN: 978-1-4200-7287-7, $99.95 / ÂŁ63.99
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