Sudipto Banerjee University of Minnesota
Bradley P Carlin University of Minnesota, Minneapolis, Minnesota, USA
Alan E Gelfand Duke University

Hierarchical Modeling and Analysis for Spatial Data

Series: Monographs on Statistics and Applied Probability

ISBN: 1-58488-410-X
Publication Date: 12/12/2003
Number of Pages: 256

A textbook format ideally suited for use as a graduate text in spatial statistics or as a supplementary text for lower-level course in spatial statistics or Bayesian statistics
Summaries of analysis methods for spatial data and Bayesian techniques and computing
A team of authors who are leading researchers in the field
Applications in epidemiology, public health, geography, and environmental science

This is the first practical treatment of Bayesian methods, modeling, and data analysis focused specifically on spatial and spatio-temporal data. Written by pre-eminent researchers in the field, it covers state-of-the-art methods for hierarchical modeling of spatial data sets, but for the uninitiated, includes gentle overviews of both spatial data analysis methods and Bayesian methodology and computing. Each chapter contains exercises, and a partial solution list is provided in an appendix. Sample WinBUGS code supporting many of the problems is available for download from the Internet.

Mara Tableman Portland State University
Jong-Sung Kim Portland State University
Series: Texts in Statistical Science Series

Survival Analysis Using S: Analysis of Time-to-Event Data

ISBN: 1-58488-408-8
Publication Date: 8/15/2003
Number of Pages: 224

Fills the need for an intermediate textbook for a first-course on survival analysis
Presents material on parametric models and corresponding procedures but does not require a high level of mathematics background
Offers a lecture-book format that presents a list of objectives at the beginning of each chapters and a summary of results for each analysis
Provides a Web site containing a wealth of supporting materials

Survival Analysis Using S: Analysis of Time-to-Event Data is designed as text for a one-semester class in survival analysis for upper-level or graduate students in statistics, biostatistics, and epidemiology. It requires only a first course in probability and statistics as a prerequisite. The authors emphasize parametric models and the advantages of hazard plots over survivor plots. Easy-to-follow S programs are interwoven throughout the book, and a supporting Web site contains S code, S-functions created by the authors, SAS codes, all of the data sets used in the book, and some additional data sets.

Brian S Everitt University of London, England, United Kingdom
Sabine Landau Institute of Psychiatry, London, England, United Kingdom

A Handbook of Statistical Analyses Using SPSS

ISBN: 1-58488-369-3
Publication Date: 11/14/2003
Number of Pages: 320

Provides concise, straightforward descriptions of how to conduct a range of statistical analyses using the latest version of SPSS
Includes exercises and model answers in each chapter relating to the data sets introduced
Presents a different type of analytical procedure in each chapter and applies it to one or more data sets
Offers a companion Web site from which all the datasets described in the book are available to download

A Handbook of Statistical Analyses Using SPSS clearly describes how to conduct a range of univariate and multivariate statistical analyses using the latest version of the Statistical Package for the Social Sciences, SPSS 11. Each chapter addresses a different type of analytical procedure applied to one or more data sets, primarily from the social and behavioral sciences areas. Each chapter also contains exercises relating to the data sets introduced, providing readers with a means to develop both their SPSS and statistical skills. Model answers to the exercises are also provided. Readers can download all of the data sets from a companion Web site furnished by the authors.

Jonathan Gross Columbia University, New York, New York, USA
Jay Yellen Rollins College, Winter Park, Florida, USA

Handbook of Graph Theory and Applications

Series: Discrete Mathematics and Its Applications

ISBN: 1-58488-090-2
Publication Date: 11/15/2003
Number of Pages: 592

Provides a unified, up-to-date resource for graph theory and its applications
Presents core definitions, facts, methods, examples, historical data, and unsolved problems
Identifies major application areas, furnishes clear explanations of the objectives in each area and presents the relevant graph-theoretic models, complete with descriptions of the special problems associated with each
Emphasizes practical results and methods
Contains a comprehensive glossary and numerous illustrations

Rapid growth and a proliferation of literature scattered throughout application areas have made it often difficult to locate information in graph theory. This new handbook provides a unified guide to graph theory and its most important applications. This single resource offers quick, convenient access to the most widely needed concepts, methods, facts, data, and terminology in graph theory, all presented in ready-to-use form. Part A addresses general concepts and methods, Part B explores applications, specifies graph theoretic models for each, presents important results, and explains current objectives. Part C comprises a glossary that helps readers makes sense out of the often inconsistent and confusing terminology used in various sectors of the field.