Biostatistics

A Methodology For the Health Sciences

Author: Gerald van Belle,Lloyd D. Fisher,Patrick J. Heagerty,Thomas Lumley

Publisher: John Wiley & Sons

ISBN: 0471602353

Category: Medical

Page: 896

View: 598

A respected introduction to biostatistics, thoroughly updated andrevised The first edition of Biostatistics: A Methodology for the HealthSciences has served professionals and students alike as a leadingresource for learning how to apply statistical methods to thebiomedical sciences. This substantially revised Second Editionbrings the book into the twenty-first century for today’saspiring and practicing medical scientist. This versatile reference provides a wide-ranging look at basicand advanced biostatistical concepts and methods in a formatcalibrated to individual interests and levels of proficiency.Written with an eye toward the use of computer applications, thebook examines the design of medical studies, descriptivestatistics, and introductory ideas of probability theory andstatistical inference; explores more advanced statistical methods;and illustrates important current uses of biostatistics. New to this edition are discussions of Longitudinal data analysis Randomized clinical trials Bayesian statistics GEE The bootstrap method Enhanced by a companion Web site providing data sets, selectedproblems and solutions, and examples from such current topics asHIV/AIDS, this is a thoroughly current, comprehensive introductionto the field.
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Biostatistics

A Methodology for the Health Sciences

Author: Lloyd D. Fisher,Gerald van Belle

Publisher: Wiley-Interscience

ISBN: N.A

Category: Medical

Page: 991

View: 3404

This versatile textbook allows students and teachers to fashion an instructional package that meets diverse learning needs. It provides a wide-ranging look at basic and advanced biostatistical concepts and methods in a format calibrated to individual interests and levels of proficiency. Each topic presentation features introductory comments, real-life examples, a step-by-step outline of the statistical procedure under discussion, an explanation of applications, and numerous practice exercises. Advanced material-which may be included in coursework at the discretion of the instructor-has been noted throughout the text with asterisks, and notes at the end of each chapter extend and enrich the primary material. Early chapters discuss the design of medical studies, descriptive statistics, and introductory ideas of probability theory and statistical inference. Later chapters explore more advanced statistical methods and illustrate important current uses of biostatistics. Statistical methods discussed include * Robustness and nonparametric statistics * Analysis of variance and covariance * Multiple comparisons * Discrimination and classification * Principal component analysis and factor analysis * Survival analysis (including life tables, product-limit estimates, and Cox proportional hazards regression) * Sample sizes for observational studies With more than 390 practice exercises, clear illustrations and graphics, and more than 130 examples, Biostatistics provides a complete detailed seminar, which encourages steady, incremental growth while acting as a catalyst for creative analysis.
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Biostatistics

Basic Concepts and Methodology for the Health Sciences

Author: Wayne W. Daniel

Publisher: N.A

ISBN: 9780470413333

Category: Biometry

Page: 960

View: 726

This ninth edition of Biostatistics: A Foundation for Analysis in the Health Sciences should appeal to the same audience for which the first eight editions were written: advanced undergraduate students, beginning graduate students, and health professionals in need of a reference book on statistical methodology.
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Introductory Biostatistics for the Health Sciences

Modern Applications Including Bootstrap

Author: Michael R. Chernick,Robert H. Friis

Publisher: John Wiley & Sons

ISBN: 0471458651

Category: Mathematics

Page: 424

View: 6802

Accessible to medicine- and/or public policy-related audiences, aswell as most statisticians. Emphasis on outliers is discussed by way of detection andtreatment. Resampling statistics software is incorporated throughout. Motivating applications are presented in light of honesttheory. Plentiful exercises are sprinkled throughout.
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Lebende Sprachen

Zeitschrift Für Fremde Sprachen in Wissenschaft und Praxis

Author: N.A

Publisher: N.A

ISBN: N.A

Category: Languages, Modern

Page: N.A

View: 2806

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Nonparametric Statistics with Applications to Science and Engineering

Author: Paul H. Kvam,Brani Vidakovic

Publisher: John Wiley & Sons

ISBN: 9780470168691

Category: Mathematics

Page: 448

View: 5165

A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to Science and Engineering begins with succinct coverage of basic results for order statistics, methods of categorical data analysis, nonparametric regression, and curve fitting methods. The authors then focus on nonparametric procedures that are becoming more relevant to engineering researchers and practitioners. The important fundamental materials needed to effectively learn and apply the discussed methods are also provided throughout the book. Complete with exercise sets, chapter reviews, and a related Web site that features downloadable MATLAB applications, this book is an essential textbook for graduate courses in engineering and the physical sciences and also serves as a valuable reference for researchers who seek a more comprehensive understanding of modern nonparametric statistical methods.
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Biostatistics, a foundation for analysis in the health sciences

Author: Wayne W. Daniel

Publisher: John Wiley & Sons

ISBN: N.A

Category: Mathematics

Page: 734

View: 4158

This classic text takes an applied and computer-oriented approach to its topical coverage. The book is intended for one or two semester courses in biostatistics at the undergraduate or graduate level offered by departments of biostatistics, statistics, mathematics, nursing and other allied health disciplines, and is also used in some departments of forestry and animal husbandry. Nearly all the examples and exercises make use of real data from actual research projects and reports from health sciences literature. Where appropriate, Minitab, SPSS and SAS commands and printouts are included as part of the examples and solutions to exercises.
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Linear Models

The Theory and Application of Analysis of Variance

Author: Brenton R. Clarke

Publisher: John Wiley & Sons

ISBN: 9780470377970

Category: Mathematics

Page: 288

View: 5897

An insightful approach to the analysis of variance in the study of linear models Linear Models explores the theory of linear models and the dynamic relationships that these models have with Analysis of Variance (ANOVA), experimental design, and random and mixed-model effects. This one-of-a-kind book emphasizes an approach that clearly explains the distribution theory of linear models and experimental design starting from basic mathematical concepts in linear algebra. The author begins with a presentation of the classic fixed-effects linear model and goes on to illustrate eight common linear models, along with the value of their use in statistics. From this foundation, subsequent chapters introduce concepts pertaining to the linear model, starting with vector space theory and the theory of least-squares estimation. An outline of the Helmert matrix is also presented, along with a thorough explanation of how the ANOVA is created in both typical two-way and higher layout designs, ultimately revealing the distribution theory. Other important topics covered include: Vector space theory The theory of least squares estimation Gauss-Markov theorem Kronecker products Diagnostic and robust methods for linear models Likelihood approaches to estimation A discussion of Bayesian theory is also included for purposes of comparison and contrast, and numerous illustrative exercises assist the reader with uncovering the nature of the models, using both classic and new data sets. Requiring only a working knowledge of basic probability and statistical inference, Linear Models is a valuable book for courses on linear models at the upper-undergraduate and graduate levels. It is also an excellent reference for practitioners who use linear models to conduct research in the fields of econometrics, psychology, sociology, biology, and agriculture.
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The EM Algorithm and Extensions

Author: Geoffrey McLachlan,Thriyambakam Krishnan

Publisher: John Wiley & Sons

ISBN: 0470191600

Category: Mathematics

Page: 384

View: 5317

The only single-source——now completely updated and revised——to offer a unified treatment of the theory, methodology, and applications of the EM algorithm Complete with updates that capture developments from the past decade, The EM Algorithm and Extensions, Second Edition successfully provides a basic understanding of the EM algorithm by describing its inception, implementation, and applicability in numerous statistical contexts. In conjunction with the fundamentals of the topic, the authors discuss convergence issues and computation of standard errors, and, in addition, unveil many parallels and connections between the EM algorithm and Markov chain Monte Carlo algorithms. Thorough discussions on the complexities and drawbacks that arise from the basic EM algorithm, such as slow convergence and lack of an in-built procedure to compute the covariance matrix of parameter estimates, are also presented. While the general philosophy of the First Edition has been maintained, this timely new edition has been updated, revised, and expanded to include: New chapters on Monte Carlo versions of the EM algorithm and generalizations of the EM algorithm New results on convergence, including convergence of the EM algorithm in constrained parameter spaces Expanded discussion of standard error computation methods, such as methods for categorical data and methods based on numerical differentiation Coverage of the interval EM, which locates all stationary points in a designated region of the parameter space Exploration of the EM algorithm's relationship with the Gibbs sampler and other Markov chain Monte Carlo methods Plentiful pedagogical elements—chapter introductions, lists of examples, author and subject indices, computer-drawn graphics, and a related Web site The EM Algorithm and Extensions, Second Edition serves as an excellent text for graduate-level statistics students and is also a comprehensive resource for theoreticians, practitioners, and researchers in the social and physical sciences who would like to extend their knowledge of the EM algorithm.
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Loss Models

From Data to Decisions

Author: Stuart A. Klugman,Harry H. Panjer,Gordon E. Willmot

Publisher: John Wiley & Sons

ISBN: 0470391332

Category: Business & Economics

Page: 784

View: 1639

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Introduction to Statistical Time Series

Author: Wayne A. Fuller

Publisher: John Wiley & Sons

ISBN: 0470317752

Category: Mathematics

Page: 728

View: 9364

The subject of time series is of considerable interest, especially among researchers in econometrics, engineering, and the natural sciences. As part of the prestigious Wiley Series in Probability and Statistics, this book provides a lucid introduction to the field and, in this new Second Edition, covers the important advances of recent years, including nonstationary models, nonlinear estimation, multivariate models, state space representations, and empirical model identification. New sections have also been added on the Wold decomposition, partial autocorrelation, long memory processes, and the Kalman filter. Major topics include: * Moving average and autoregressive processes * Introduction to Fourier analysis * Spectral theory and filtering * Large sample theory * Estimation of the mean and autocorrelations * Estimation of the spectrum * Parameter estimation * Regression, trend, and seasonality * Unit root and explosive time series To accommodate a wide variety of readers, review material, especially on elementary results in Fourier analysis, large sample statistics, and difference equations, has been included.
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Visual Statistics

Seeing Data with Dynamic Interactive Graphics

Author: Forrest W. Young,Pedro M. Valero-Mora,Michael Friendly

Publisher: John Wiley & Sons

ISBN: 1118165411

Category: Mathematics

Page: 363

View: 1980

A visually intuitive approach to statistical data analysis Visual Statistics brings the most complex and advanced statisticalmethods within reach of those with little statistical training byusing animated graphics of the data. Using ViSta: The VisualStatistics System-developed by Forrest Young and Pedro Valero-Moraand available free of charge on the Internet-students can easilycreate fully interactive visualizations from relevant mathematicalstatistics, promoting perceptual and cognitive understanding of thedata's story. An emphasis is placed on a paradigm for understandingdata that is visual, intuitive, geometric, and active, rather thanone that relies on convoluted logic, heavy mathematics, systems ofalgebraic equations, or passive acceptance of results. A companion Web site complements the book by further demonstratingthe concept of creating interactive and dynamic graphics. The bookprovides users with the opportunity to view the graphics in adynamic way by illustrating how to analyze statistical data andexplore the concepts of visual statistics. Visual Statistics addresses and features the followingtopics: * Why use dynamic graphics? * A history of statistical graphics * Visual statistics and the graphical user interface * Visual statistics and the scientific method * Character-based statistical interface objects * Graphics-based statistical interfaces * Visualization for exploring univariate data This is an excellent textbook for undergraduate courses in dataanalysis and regression, for students majoring or minoring instatistics, mathematics, science, engineering, and computerscience, as well as for graduate-level courses in mathematics. Thebook is also ideal as a reference/self-study guide for engineers,scientists, and mathematicians. With contributions by highly regarded professionals in the field,Visual Statistics not only improves a student's understanding ofstatistics, but also builds confidence to overcome problems thatmay have previously been intimidating.
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Statistical Rules of Thumb

Author: Gerald van Belle

Publisher: John Wiley & Sons

ISBN: 1118210360

Category: Mathematics

Page: 304

View: 4017

Praise for the First Edition: "For a beginner [this book] is a treasure trove; for anexperienced person it can provide new ideas on how better to pursuethe subject of applied statistics." —Journal of Quality Technology Sensibly organized for quick reference, Statistical Rules ofThumb, Second Edition compiles simple rules that arewidely applicable, robust, and elegant, and each captures keystatistical concepts. This unique guide to the use of statisticsfor designing, conducting, and analyzing research studiesillustrates real-world statistical applications through examplesfrom fields such as public health and environmental studies. Alongwith an insightful discussion of the reasoning behind everytechnique, this easy-to-use handbook also conveys the variouspossibilities statisticians must think of when designing andconducting a study or analyzing its data. Each chapter presents clearly defined rules related toinference, covariation, experimental design, consultation, and datarepresentation, and each rule is organized and discussed under fivesuccinct headings: introduction; statement and illustration of therule; the derivation of the rule; a concluding discussion; andexploration of the concept's extensions. The author also introducesnew rules of thumb for topics such as sample size for ratioanalysis, absolute and relative risk, ANCOVA cautions, anddichotomization of continuous variables. Additional features of theSecond Edition include: Additional rules on Bayesian topics New chapters on observational studies and Evidence-BasedMedicine (EBM) Additional emphasis on variation and causation Updated material with new references, examples, and sources A related Web site provides a rich learning environment andcontains additional rules, presentations by the author, and amessage board where readers can share their own strategies anddiscoveries. Statistical Rules of Thumb, SecondEdition is an ideal supplementary book for courses inexperimental design and survey research methods at theupper-undergraduate and graduate levels. It also serves as anindispensable reference for statisticians, researchers,consultants, and scientists who would like to develop anunderstanding of the statistical foundations of their researchefforts. A related website www.vanbelle.org provides additionalrules, author presentations and more.
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Theory of Preliminary Test and Stein-Type Estimation with Applications

Author: A. K. Md. Ehsanes Saleh

Publisher: John Wiley & Sons

ISBN: 0471773743

Category: Mathematics

Page: 656

View: 9180

Theory of Preliminary Test and Stein-Type Estimation withApplications provides a com-prehensive account of the theory andmethods of estimation in a variety of standard models used inapplied statistical inference. It is an in-depth introduction tothe estimation theory for graduate students, practitioners, andresearchers in various fields, such as statistics, engineering,social sciences, and medical sciences. Coverage of the material isdesigned as a first step in improving the estimates before applyingfull Bayesian methodology, while problems at the end of eachchapter enlarge the scope of the applications. This book contains clear and detailed coverage of basic terminologyrelated to various topics, including: * Simple linear model; ANOVA; parallelism model; multipleregression model with non-stochastic and stochastic constraints;regression with autocorrelated errors; ridge regression; andmultivariate and discrete data models * Normal, non-normal, and nonparametric theory of estimation * Bayes and empirical Bayes methods * R-estimation and U-statistics * Confidence set estimation
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Periodically Correlated Random Sequences

Spectral Theory and Practice

Author: Harry L. Hurd,Abolghassem Miamee

Publisher: John Wiley & Sons

ISBN: 9780470182826

Category: Mathematics

Page: 384

View: 2159

Uniquely combining theory, application, and computing, this book explores the spectral approach to time series analysis The use of periodically correlated (or cyclostationary) processes has become increasingly popular in a range of research areas such as meteorology, climate, communications, economics, and machine diagnostics. Periodically Correlated Random Sequences presents the main ideas of these processes through the use of basic definitions along with motivating, insightful, and illustrative examples. Extensive coverage of key concepts is provided, including second-order theory, Hilbert spaces, Fourier theory, and the spectral theory of harmonizable sequences. The authors also provide a paradigm for nonparametric time series analysis including tests for the presence of PC structures. Features of the book include: An emphasis on the link between the spectral theory of unitary operators and the correlation structure of PC sequences A discussion of the issues relating to nonparametric time series analysis for PC sequences, including estimation of the mean, correlation, and spectrum A balanced blend of historical background with modern application-specific references to periodically correlated processes An accompanying Web site that features additional exercises as well as data sets and programs written in MATLAB® for performing time series analysis on data that may have a PC structure Periodically Correlated Random Sequences is an ideal text on time series analysis for graduate-level statistics and engineering students who have previous experience in second-order stochastic processes (Hilbert space), vector spaces, random processes, and probability. This book also serves as a valuable reference for research statisticians and practitioners in areas of probability and statistics such as time series analysis, stochastic processes, and prediction theory.
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The Construction of Optimal Stated Choice Experiments

Theory and Methods

Author: Deborah J. Street,Leonie Burgess

Publisher: John Wiley & Sons

ISBN: 9780470148556

Category: Mathematics

Page: 320

View: 8027

The most comprehensive and applied discussion of stated choice experiment constructions available The Construction of Optimal Stated Choice Experiments provides an accessible introduction to the construction methods needed to create the best possible designs for use in modeling decision-making. Many aspects of the design of a generic stated choice experiment are independent of its area of application, and until now there has been no single book describing these constructions. This book begins with a brief description of the various areas where stated choice experiments are applicable, including marketing and health economics, transportation, environmental resource economics, and public welfare analysis. The authors focus on recent research results on the construction of optimal and near-optimal choice experiments and conclude with guidelines and insight on how to properly implement these results. Features of the book include: Construction of generic stated choice experiments for the estimation of main effects only, as well as experiments for the estimation of main effects plus two-factor interactions Constructions for choice sets of any size and for attributes with any number of levels A discussion of designs that contain a none option or a common base option Practical techniques for the implementation of the constructions Class-tested material that presents theoretical discussion of optimal design Complete and extensive references to the mathematical and statistical literature for the constructions Exercise sets in most chapters, which reinforce the understanding of the presented material The Construction of Optimal Stated Choice Experiments serves as an invaluable reference guide for applied statisticians and practitioners in the areas of marketing, health economics, transport, and environmental evaluation. It is also ideal as a supplemental text for courses in the design of experiments, decision support systems, and choice models. A companion web site is available for readers to access web-based software that can be used to implement the constructions described in the book.
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Univariate Discrete Distributions

Author: Norman L. Johnson,Adrienne W. Kemp,Samuel Kotz

Publisher: John Wiley & Sons

ISBN: 0471715808

Category: Mathematics

Page: 646

View: 545

This Set Contains: Continuous Multivariate Distributions, Volume 1, Models andApplications, 2nd Edition by Samuel Kotz, N. Balakrishnan andNormal L. Johnson Continuous Univariate Distributions, Volume 1, 2nd Editionby Samuel Kotz, N. Balakrishnan and Normal L. Johnson Continuous Univariate Distributions, Volume 2, 2nd Editionby Samuel Kotz, N. Balakrishnan and Normal L. Johnson Discrete Multivariate Distributions by Samuel Kotz, N.Balakrishnan and Normal L. Johnson Univariate Discrete Distributions, 3rd Edition by SamuelKotz, N. Balakrishnan and Normal L. Johnson Discover the latest advances in discrete distributionstheory The Third Edition of the critically acclaimedUnivariate Discrete Distributions provides a self-contained,systematic treatment of the theory, derivation, and application ofprobability distributions for count data. Generalized zeta-functionand q-series distributions have been added and are covered indetail. New families of distributions, including Lagrangian-typedistributions, are integrated into this thoroughly revised andupdated text. Additional applications of univariate discretedistributions are explored to demonstrate the flexibility of thispowerful method. A thorough survey of recent statistical literature drawsattention to many new distributions and results for the classicaldistributions. Approximately 450 new references along with severalnew sections are introduced to reflect the current literature andknowledge of discrete distributions. Beginning with mathematical, probability, and statisticalfundamentals, the authors provide clear coverage of the key topicsin the field, including: Families of discrete distributions Binomial distribution Poisson distribution Negative binomial distribution Hypergeometric distributions Logarithmic and Lagrangian distributions Mixture distributions Stopped-sum distributions Matching, occupancy, runs, and q-series distributions Parametric regression models and miscellanea Emphasis continues to be placed on the increasing relevance ofBayesian inference to discrete distribution, especially with regardto the binomial and Poisson distributions. New derivations ofdiscrete distributions via stochastic processes and random walksare introduced without unnecessarily complex discussions ofstochastic processes. Throughout the Third Edition, extensiveinformation has been added to reflect the new role ofcomputer-based applications. With its thorough coverage and balanced presentation of theoryand application, this is an excellent and essential reference forstatisticians and mathematicians.
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The Theory of Measures and Integration

Author: Eric M. Vestrup

Publisher: John Wiley & Sons

ISBN: 0470317957

Category: Mathematics

Page: 624

View: 1845

An accessible, clearly organized survey of the basic topics of measure theory for students and researchers in mathematics, statistics, and physics In order to fully understand and appreciate advanced probability, analysis, and advanced mathematical statistics, a rudimentary knowledge of measure theory and like subjects must first be obtained. The Theory of Measures and Integration illuminates the fundamental ideas of the subject-fascinating in their own right-for both students and researchers, providing a useful theoretical background as well as a solid foundation for further inquiry. Eric Vestrup's patient and measured text presents the major results of classical measure and integration theory in a clear and rigorous fashion. Besides offering the mainstream fare, the author also offers detailed discussions of extensions, the structure of Borel and Lebesgue sets, set-theoretic considerations, the Riesz representation theorem, and the Hardy-Littlewood theorem, among other topics, employing a clear presentation style that is both evenly paced and user-friendly. Chapters include: * Measurable Functions * The Lp Spaces * The Radon-Nikodym Theorem * Products of Two Measure Spaces * Arbitrary Products of Measure Spaces Sections conclude with exercises that range in difficulty between easy "finger exercises"and substantial and independent points of interest. These more difficult exercises are accompanied by detailed hints and outlines. They demonstrate optional side paths in the subject as well as alternative ways of presenting the mainstream topics. In writing his proofs and notation, Vestrup targets the person who wants all of the details shown up front. Ideal for graduate students in mathematics, statistics, and physics, as well as strong undergraduates in these disciplines and practicing researchers, The Theory of Measures and Integration proves both an able primary text for a real analysis sequence with a focus on measure theory and a helpful background text for advanced courses in probability and statistics.
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Numerical Issues in Statistical Computing for the Social Scientist

Author: Micah Altman,Jeff Gill,Michael P. McDonald

Publisher: John Wiley & Sons

ISBN: 0471475742

Category: Mathematics

Page: 323

View: 6572

At last—a social scientist's guide through the pitfalls ofmodern statistical computing Addressing the current deficiency in the literature onstatistical methods as they apply to the social and behavioralsciences, Numerical Issues in Statistical Computing for the SocialScientist seeks to provide readers with a unique practicalguidebook to the numerical methods underlying computerizedstatistical calculations specific to these fields. The authorsdemonstrate that knowledge of these numerical methods and how theyare used in statistical packages is essential for making accurateinferences. With the aid of key contributors from both the socialand behavioral sciences, the authors have assembled a rich set ofinterrelated chapters designed to guide empirical social scientiststhrough the potential minefield of modern statisticalcomputing. Uniquely accessible and abounding in modern-day tools, tricks,and advice, the text successfully bridges the gap between thecurrent level of social science methodology and the moresophisticated technical coverage usually associated with thestatistical field. Highlights include: A focus on problems occurring in maximum likelihoodestimation Integrated examples of statistical computing (using softwarepackages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS,WinBUGS, and MATLAB®) A guide to choosing accurate statistical packages Discussions of a multitude of computationally intensivestatistical approaches such as ecological inference, Markov chainMonte Carlo, and spatial regression analysis Emphasis on specific numerical problems, statisticalprocedures, and their applications in the field Replications and re-analysis of published social scienceresearch, using innovative numerical methods Key numerical estimation issues along with the means ofavoiding common pitfalls A related Web site includes test data for use in demonstratingnumerical problems, code for applying the original methodsdescribed in the book, and an online bibliography of Web resourcesfor the statistical computation Designed as an independent research tool, a professionalreference, or a classroom supplement, the book presents awell-thought-out treatment of a complex and multifaceted field.
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