This text describes regression-based approaches to analyzing longitudinal and repeated measures data. It emphasizes statistical models, discusses the relationships between different approaches, and uses real data to illustrate practical applications. It uses commercially available software when it exists and illustrates the program code and output. The data appendix provides many real data sets-beyond those used for the examples-which can serve as the basis for exercises.
Bridging law, genetics, and statistics, this book is an authoritative history of the long and tortuous process by which DNA science has been integrated into the American legal system. In a history both scientifically sophisticated and comprehensible to the nonspecialist, David Kaye weaves together molecular biology, population genetics, the legal rules of evidence, and theories of statistical reasoning as he describes the struggles between prosecutors and defense counsel over the admissibility of genetic proof of identity. Combining scientific exposition with stories of criminal investigations, scientific and legal hubris, and distortions on all sides, Kaye shows how the adversary system exacerbated divisions among scientists, how lawyers and experts obfuscated some issues and clarified others, how probability and statistics were manipulated and misunderstood, and how the need to convince lay judges influenced the scientific research. Looking to the future, Kaye uses probability theory to clarify legal concepts of relevance and probative value, and describes alternatives to race-based DNA profile frequencies. Essential reading for lawyers, judges, and expert witnesses in DNA cases, The Double Helix and the Law of Evidence is an informative and provocative contribution to the interdisciplinary study of law and science.
The term probability can be used in two main senses. In the frequency interpretation it is a limiting ratio in a sequence of repeatable events. In the Bayesian view, probability is a mental construct representing uncertainty. This 2002 book is about these two types of probability and investigates how, despite being adopted by scientists and statisticians in the eighteenth and nineteenth centuries, Bayesianism was discredited as a theory of scientific inference during the 1920s and 1930s. Through the examination of a dispute between two British scientists, the author argues that a choice between the two interpretations is not forced by pure logic or the mathematics of the situation, but depends on the experiences and aims of the individuals involved. The book should be of interest to students and scientists interested in statistics and probability theories and to general readers with an interest in the history, sociology and philosophy of science.
Describes ways of assessing forensic science evidence and the means of communicating the assessment to a court of law. The aim of this work is to ensure that the courts consider seriously the probability of the evidence of association.
A novel and robust framework for the operational and legal analysis of recovering fugitives abroad, Bringing International Fugitives to Justice addresses how states, working alone, in cooperation, or with third-party intervention, strive to secure the custody of fugitives in order to bring them to justice - for prosecution or punishment purposes - while evaluating the lawfulness of those pursuit efforts. The book introduces redefined terms and new concepts to add precision to the discourse; sets forth comprehensive typologies, including of extradition arrangements and impediments; and provides a mapping to account for the full range of means and methods - extradition, collateral and remedial approaches to extradition, and full-scale and fallback alternatives to extradition -by which international fugitives can be retrieved. The study considers the judicial, diplomatic, and policy consequences of reliance on the more aggressive or controversial alternatives, proffering recommendations that, if adopted, could facilitate the recovery of fugitives while minimizing associated risks.
This new edition of the book will be produced in two versions. The textbook will include a CD-Rom with two videotaped lectures by the authors. This book translates biostatistics in the health sciences literature with clarity and irreverence. Students and practitioners alike, applaud Biostatistics as the practical guide that exposes them to every statistical test they may encounter, with careful conceptual explanations and a minimum of algebra. What's New? The new Bare Essentials reflects recent advances in statistics, as well as time-honored methods. For example, "hierarchical linear modeling" which first appeared in psychology journals and only now is described in medical literature. Also new, is a chapter on testing for equivalence and non-inferiority. As well as a chapter with information to get started with the computer statistics program, SPSS. Free of calculations and jargon, Bare Essentials speaks so plainly that you won't need a technical dictionary. No math, all concepts. The objective is to enable you to determine if the research results are applicable to your own patients. Throughout the guide, you'll find highlights of areas in which researchers misuse or misinterpret statistical tests. We have labeled these "C.R.A.P. Detectors" (Convoluted Reasoning and Anti-intellectual Pomposity), which help you to identify faulty methodology and misuse of statistics.
Repeated measures data arise when the same characteristic is measured on each case or subject at several times or under several conditions. There is a multitude of techniques available for analysing such data and in the past this has led to some confusion. This book describes the whole spectrum of approaches, beginning with very simple and crude methods, working through intermediate techniques commonly used by consultant statisticians, and concluding with more recent and advanced methods. Those covered include multiple testing, response feature analysis, univariate analysis of variance approaches, multivariate analysis of variance approaches, regression models, two-stage line models, approaches to categorical data and techniques for analysing crossover designs. The theory is illustrated with examples, using real data brought to the authors during their work as statistical consultants.
Following in the footsteps of its bestselling predecessors, the Handbook of Parametric and Nonparametric Statistical Procedures, Fifth Edition provides researchers, teachers, and students with an all-inclusive reference on univariate, bivariate, and multivariate statistical procedures.New in the Fifth Edition:Substantial updates and new material th
This book expertly guides the reader through all stages involved in undertaking quantitative psychological research, from accessing the relevant literature, through designing and conducting a study, analysing and interpreting data, and finally reporting the research. This third edition includes two new chapters - on preliminary checking of data and allowing for additional variables when comparing the means of different conditions - and expands on original topics such as choosing sample sizes and how to test for mediation effects. It also contains increased coverage of tests and further detail of techniques and terms which psychologists will meet when working with those in the medical professions. As the chapters focus on choosing appropriate statistical tests and how to interpret and report them (rather than the detailed calculations, which appear in appendices), the reader is able to gain an understanding of a test without being interrupted by the need to understand the complex mathematics behind it. In addition, for the first time, the book is accompanied by an online bank of multiple choice questions. The book helps readers to: Locate reports of relevant existing research Design research while adhering to ethical principles Identify various methods which can be used to ask questions or observe behaviour Choose appropriate samples Display and analyse findings numerically and graphically to test hypotheses Report psychological research in a variety of ways. As such, the book is suitable for psychology students and professionals at all levels, and is particularly useful to those working in Health and Clinical Psychology.
Sport Industry Research and Analysis offers a straightforward, no nonsense approach to research design and statistical analyses in sport organizations. This fully revised and updated new edition describes the research process, from identifying a research question to analyzing data, and uses real world scenarios to help students and industry professionals understand how to conduct research and apply the results in their wider work. The book includes clear, step-by-step instructions for the analysis and interpretation of data. It explains how to use Excel and SPSS for every key statistic and statistical technique, with screenshots illustrating every step and additional scenarios providing further context. "In Practice" contributions from sport industry professionals demonstrate how these practitioners use statistical analyses in their everyday tasks, and this new edition includes expanded sections on conducting a literature review and research ethics, as well as ancillary materials for instructors including slides, test questions, data files, answer sheets, and videos. This is the clearest and most easy-to-use guide to research and analysis techniques in sport, helping the reader to build essential skills and confidence in using statistics, vital to support decision-making in any sport enterprise. It is an essential text for any sport business research methods course, and an invaluable reference for all sport industry professionals.
Quantitative Psychological Research: A Student's Handbook is a thoroughly revised and updated version of David Clark-Carter's extremely successful Doing Quantitative Psychological Research: From Design to Report. This comprehensive handbook verses the reader in a wide range of statistical tools in order to ensure that quantitative research and the analysis of its findings go beyond mere description towards sound hypothesis formulation and testing. The entire research process is covered in detail, from selection of research design through to analysis and presentation of results. Core topics examined include: * variables and the validity of research designs * summarizing and describing data: numerous practical examples are given of both graphical and numerical methods * reporting research both verbally and in writing * univarate and bi-varate statistics: multivariate analysis and meta-analysis also benefit from dedicated chapters. This catch-all reference book will prove invaluable to both undergraduate and postgraduate students, bringing clarity and reliability to each stage of the quantitative research process.
In Turkey, Iran, Iraq, and Syria, central governments historically pursued mono-nationalist ideologies and repressed Kurdish identity. As evidenced by much unrest and a great many Kurdish revolts in all these states since the 1920s, however, the Kurds manifested strong resistance towards ethnic chauvinism. What sorts of authoritarian state policies have Turkey, Iraq, Iran and Syria relied on to contain the Kurds over the years? Can meaningful democratization and liberalization in any of these states occur without a fundamental change vis-à-vis their Kurdish minorities? To what extent does the Kurdish issue function as both a barrier and key to democratization in four of the most important states of the Middle East? While many commentators on the Middle East stress the importance of resolving the Arab-Israeli dispute for achieving 'peace in the Middle East,' this book asks whether or not the often overlooked Kurdish issue may constitute a more important fulcrum for change in the region, especially in light of the 'Arab Spring' and recent changes in Turkey, Iraq, Iran and Syria.
At least since the French Revolution, France has the peculair distinction of simultaneously fascinating, charming and exasperating its neighbours and foreign observers. Contemporary France provides an essential introduction for students of French politics and society, exploring contemporary developments while placing them in a deeper historical, intellectual, cultural and social context that makes for insightful analysis. Thus, chapters on France's economic policy and welfare state, its foreign and European policies and its political movements and recent institutional developments are informed by an analysis of the country's unique political and institutional traditions, distinct forms of nationalism and citizenship, dynamic intellectual life and recent social trends. Summaries of key political, economic and social movements and events are displayed as exhibits.
How might one determine if a financial institution is taking risk in a balanced and productive manner? A powerful tool to address this question is economic capital, which is a model-based measure of the amount of equity that an entity must hold to satisfactorily offset its risk-generating activities. This book, with a particular focus on the credit-risk dimension, pragmatically explores real-world economic-capital methodologies and applications. It begins with the thorny practical issues surrounding the construction of an (industrial-strength) credit-risk economic-capital model, defensibly determining its parameters, and ensuring its efficient implementation. It then broadens its gaze to examine various critical applications and extensions of economic capital; these include loan pricing, the computation of loan impairments, and stress testing. Along the way, typically working from first principles, various possible modelling choices and related concepts are examined. The end result is a useful reference for students and practitioners wishing to learn more about a centrally important financial-management device.
One of the all-time chess greats, José Raúl Capablanca (1888–1942), displays his brilliant imaginative maneuvers and strategies in 203 of his lesser matches and exhibitions. Includes his complete chess record.
This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability and skewness. The authors have developed statistical techniques--such as formal fitting methods and less formal graphical techniques-- that can be applied to many problems across a range of disciplines, including pharmacokinetics, econometrics, biochemical assays, and fisheries research. While the main focus of the book in on data transformation and weighting, it also draws upon ideas from diverse fields such as influence diagnostics, robustness, bootstrapping, nonparametric data smoothing, quasi-likelihood methods, errors-in-variables, and random coefficients. The authors discuss the computation of estimates and give numerous examples using real data. The book also includes an extensive treatment of estimating variance functions in regression.
Biplots are the multivariate analog of scatter plots, approximating the multivariate distribution of a sample in a few dimensions to produce a graphic display. In addition, they superimpose representations of the variables on this display so that the relationships between the sample and the variable can be studied. Like scatter plots, biplots are useful for detecting patterns and for displaying the results found by more formal methods of analysis. In recent years the theory of biplots has been considerably extended. The approach adopted here is geometric, permitting a natural integration of well-known methods, such as components analysis, correspondence analysis, and canonical variate analysis as well as some newer and less well-known methods, such as nonlinear biplots and biadditive models.
Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area. This book provides a unified treatment of Bayesian analysis of models based on stochastic processes, covering the main classes of stochastic processing including modeling, computational, inference, forecasting, decision making and important applied models. Key features: Explores Bayesian analysis of models based on stochastic processes, providing a unified treatment. Provides a thorough introduction for research students. Computational tools to deal with complex problems are illustrated along with real life case studies Looks at inference, prediction and decision making. Researchers, graduate and advanced undergraduate students interested in stochastic processes in fields such as statistics, operations research (OR), engineering, finance, economics, computer science and Bayesian analysis will benefit from reading this book. With numerous applications included, practitioners of OR, stochastic modelling and applied statistics will also find this book useful.
THE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATA—NOW IN A VALUABLE NEW EDITION Since publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study. Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical, and other health-related research. This book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory. It offers a clear and accessible presentation of modern modeling techniques supplemented with real-world examples and case studies. Key topics covered include: variable selection, identification of the scale of continuous covariates, the role of interactions in the model, assessment of fit and model assumptions, regression diagnostics, recurrent event models, frailty models, additive models, competing risk models, and missing data. Features of the Second Edition include: Expanded coverage of interactions and the covariate-adjusted survival functions The use of the Worchester Heart Attack Study as the main modeling data set for illustrating discussed concepts and techniques New discussion of variable selection with multivariable fractional polynomials Further exploration of time-varying covariates, complex with examples Additional treatment of the exponential, Weibull, and log-logistic parametric regression models Increased emphasis on interpreting and using results as well as utilizing multiple imputation methods to analyze data with missing values New examples and exercises at the end of each chapter Analyses throughout the text are performed using Stata® Version 9, and an accompanying FTP site contains the data sets used in the book. Applied Survival Analysis, Second Edition is an ideal book for graduate-level courses in biostatistics, statistics, and epidemiologic methods. It also serves as a valuable reference for practitioners and researchers in any health-related field or for professionals in insurance and government.
International and Transnational Criminal Law, Fourth Edition, by David J. Luban, Julie R. O’Sullivan, David P. Stewart, and Neha Jain covers both international criminal law and the application of U.S. criminal law transnationally. This comprehensive and versatile book has chapters on each of the core crimes (aggression, genocide, crimes against humanity, and war crimes) as well as terrorism and torture. It has separate chapters on the international tribunals from Nuremberg on and the ICC. Other chapters treat modes of liability, defenses, crimes against women, and alternatives to criminal prosecution in post-conflict societies. It also covers U.S. criminal law in transnational contexts, including money laundering, Foreign Corrupt Practices Act, trafficking, and terrorism. In addition, it includes chapters on extradition, evidence gathering abroad, comparative criminal procedure and comparative sentencing, and U.S. constitutional rights abroad. Introductory chapters on the nature of international criminal law, transnational jurisdiction, and the basics of public international law make the book accessible to students (as well as government lawyers and private practitioners) with no prior background in this increasingly important field. New to the Fourth Edition: Recent developments in the international tribunals, including the Special Court for the Central African Republic and Colombia’s Special Jurisdiction for Peace. Updates on post-Morrison jurisdictional developments, including new cases and exposition. Expanded treatment of aggression, including coverage of the Russia-Ukraine conflict. Comprehensive revision of the chapter on obtaining evidence abroad, with greater emphasis on difficulties facing defense counsel. Updates on ICC jurisprudence, including developments on command responsibility and criminal defenses. Updated genocide chapter, including a new section on cultural genocide and discussion of the Ukraine v. Russia ICJ litigation. Professors and students will benefit from: Versatility: The book can be used for courses on international criminal law and also for courses on U.S. criminal law applied across borders. Self-contained introductory chapters on basic public international law, transnational jurisdiction, and the nature of criminal law. A detailed treatment of “headline” issues including torture, terrorism, war crimes, and the Russia-Ukraine conflict. Readable background on historical context.
Bayesian statistical methods have become widely used for data analysis and modelling in recent years, and the BUGS software has become the most popular software for Bayesian analysis worldwide. Authored by the team that originally developed this software, The BUGS Book provides a practical introduction to this program and its use. The text presents complete coverage of all the functionalities of BUGS, including prediction, missing data, model criticism, and prior sensitivity. It also features a large number of worked examples and a wide range of applications from various disciplines. The book introduces regression models, techniques for criticism and comparison, and a wide range of modelling issues before going into the vital area of hierarchical models, one of the most common applications of Bayesian methods. It deals with essentials of modelling without getting bogged down in complexity. The book emphasises model criticism, model comparison, sensitivity analysis to alternative priors, and thoughtful choice of prior distributions—all those aspects of the "art" of modelling that are easily overlooked in more theoretical expositions. More pragmatic than ideological, the authors systematically work through the large range of "tricks" that reveal the real power of the BUGS software, for example, dealing with missing data, censoring, grouped data, prediction, ranking, parameter constraints, and so on. Many of the examples are biostatistical, but they do not require domain knowledge and are generalisable to a wide range of other application areas. Full code and data for examples, exercises, and some solutions can be found on the book’s website.
This highly effective guide is designed to help attorneys differentiate expert testimony that is scientifically well-established from authoritative pronouncements that are mainly speculative. Building on the foundation of Jay Ziskin's classic work, this updated text blends the best of previous editions with discussion of positive scientific advances in the field to provide practical guidance for experts and lawyers alike. Major contributors in the field summarize the state of the literature in numerous key areas of the behavioral sciences and law. Working from these foundations, the text provides extensive guidance, tips, and strategies for improving the quality of legal evaluations and testimony, appraising the trustworthiness of experts' opinions, and as follows, bolstering or challenging conclusions in a compelling manner. Distinctive features of this text include detailed coverage of admissibility and Daubert challenges, with unique chapters written by an eminently qualified judge and attorney; hundreds of helpful suggestions covering such topics as forensic evaluations, discovery, and the conduct of depositions and cross-examinations; and two chapters on the use of visuals to enhance communication and persuasiveness, including a unique chapter with over 125 model visuals for cases in psychology and law. More than ever, the sixth edition is an invaluable teaching tool and resource, making it a 'must have' for mental health professionals and attorneys"--
Statisticians and applied scientists must often select a model to fit empirical data. This book discusses the philosophy and strategy of selecting such a model using the information theory approach pioneered by Hirotugu Akaike. This approach focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. The book includes practical applications in biology and environmental science.
Handbook of Behavioral Medicine presents a comprehensive overview of the current use of behavioral science techniques in the prevention, diagnosis, and treatment of various health related disorders. Features contributions from a variety of internationally recognized experts in behavioral medicine and related fields Includes authors from education, social work, and physical therapy Addresses foundational issues in behavioral medicine in Volume 1, including concepts, theories, treatments, doctor/patient relationships, common medical problems, behavioral technologies, assessment, and methodologies Focuses on medical interface in Volume 2, including issues relating to health disorders and specialties; social work, medical sociology, and psychosocial aspects; and topics relating to education and health 2 Volumes
In Rational and Irrational Beliefs: Research, Theory, and Clinical Practice, leading scholars, researchers, and practitioners of rational emotive behavior therapy (REBT) and other cognitive-behavioral therapies (CBTs) share their perspectives and empirical findings on the nature of rational and irrational beliefs, the role of beliefs as mediators of functional and dysfunctional emotions and behaviors, and clinical approaches to modifying irrational beliefs, enhancing rational beliefs, and adaptive coping in the face of stressful life events. Offering a comprehensive and cohesive approach to understanding REBT/CBT and its central constructs of rational and irrational beliefs, contributors review a steadily accumulating empirical literature indicating that irrational beliefs are associated with a wide range of problems in living and that exposure to rational self-statements can decrease anxiety and other psychological symptoms, and play a valuable role in health promotion and disease prevention. Contributors also identify new frontiers of research and theory, including the link between irrational beliefs and other cognitive processes such as memory, psychophysiological responses, and evolutionary and cultural determinants of rational and irrational beliefs. A truly accessible, state-of-the-science summary of REBT/CBT research and clinical applications, Rational and Irrational Beliefs is an invaluable resource for psychotherapy practitioners of all theoretical orientations, as well as instructors, students, and academic psychologists.
The second edition of this practical book equips social science researchers to apply the latest Bayesian methodologies to their data analysis problems. It includes new chapters on model uncertainty, Bayesian variable selection and sparsity, and Bayesian workflow for statistical modeling. Clearly explaining frequentist and epistemic probability and prior distributions, the second edition emphasizes use of the open-source RStan software package. The text covers Hamiltonian Monte Carlo, Bayesian linear regression and generalized linear models, model evaluation and comparison, multilevel modeling, models for continuous and categorical latent variables, missing data, and more. Concepts are fully illustrated with worked-through examples from large-scale educational and social science databases, such as the Program for International Student Assessment and the Early Childhood Longitudinal Study. Annotated RStan code appears in screened boxes; the companion website (www.guilford.com/kaplan-materials) provides data sets and code for the book's examples. New to This Edition *Utilizes the R interface to Stan--faster and more stable than previously available Bayesian software--for most of the applications discussed. *Coverage of Hamiltonian MC; Cromwell’s rule; Jeffreys' prior; the LKJ prior for correlation matrices; model evaluation and model comparison, with a critique of the Bayesian information criterion; variational Bayes as an alternative to Markov chain Monte Carlo (MCMC) sampling; and other new topics. *Chapters on Bayesian variable selection and sparsity, model uncertainty and model averaging, and Bayesian workflow for statistical modeling.
Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.
Discusses how statistics have changed the field of science in the twentieth century, focusing on the theories and ideas of famous scientists and thinkers.
A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.
Clarifies modern data analysis through nonparametric density estimation for a complete working knowledge of the theory and methods Featuring a thoroughly revised presentation, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition maintains an intuitive approach to the underlying methodology and supporting theory of density estimation. Including new material and updated research in each chapter, the Second Edition presents additional clarification of theoretical opportunities, new algorithms, and up-to-date coverage of the unique challenges presented in the field of data analysis. The new edition focuses on the various density estimation techniques and methods that can be used in the field of big data. Defining optimal nonparametric estimators, the Second Edition demonstrates the density estimation tools to use when dealing with various multivariate structures in univariate, bivariate, trivariate, and quadrivariate data analysis. Continuing to illustrate the major concepts in the context of the classical histogram, Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition also features: Over 150 updated figures to clarify theoretical results and to show analyses of real data sets An updated presentation of graphic visualization using computer software such as R A clear discussion of selections of important research during the past decade, including mixture estimation, robust parametric modeling algorithms, and clustering More than 130 problems to help readers reinforce the main concepts and ideas presented Boxed theorems and results allowing easy identification of crucial ideas Figures in color in the digital versions of the book A website with related data sets Multivariate Density Estimation: Theory, Practice, and Visualization, Second Edition is an ideal reference for theoretical and applied statisticians, practicing engineers, as well as readers interested in the theoretical aspects of nonparametric estimation and the application of these methods to multivariate data. The Second Edition is also useful as a textbook for introductory courses in kernel statistics, smoothing, advanced computational statistics, and general forms of statistical distributions.
The authors examine the conditions under which democratic events, including elections, cabinet formations, and government dissolutions, affect asset markets. Where these events have less predictable outcomes, market returns are depressed and volatility increases. In contrast, where market actors can forecast the result, returns do not exhibit any unusual behavior. Further, political expectations condition how markets respond to the political process. When news causes market actors to update their political beliefs, market actors reallocate their portfolios, and overall market behavior changes. To measure political information, Professors Bernhard and Leblang employ sophisticated models of the political process. They draw on a variety of models of market behavior, including the efficient markets hypothesis, capital asset pricing model, and arbitrage pricing theory, to trace the impact of political events on currency, stock, and bond markets. The analysis will appeal to academics, graduate students, and advanced undergraduates across political science, economics, and finance.
This text assists mental health clinicians and traumatologists in 'making the bridge' between their clinical knowledge and skills and the unique, complex, chaotic and highly political field of disaster. It combines information from prior research with the authors' practical experience in the field.
This volume collects the texts of five courses given in the Arithmetic Geometry Research Programme 2009-2010 at the CRM Barcelona. All of them deal with characteristic p global fields; the common theme around which they are centered is the arithmetic of L-functions (and other special functions), investigated in various aspects. Three courses examine some of the most important recent ideas in the positive characteristic theory discovered by Goss (a field in tumultuous development, which is seeing a number of spectacular advances): they cover respectively crystals over function fields (with a number of applications to L-functions of t-motives), gamma and zeta functions in characteristic p, and the binomial theorem. The other two are focused on topics closer to the classical theory of abelian varieties over number fields: they give respectively a thorough introduction to the arithmetic of Jacobians over function fields (including the current status of the BSD conjecture and its geometric analogues, and the construction of Mordell-Weil groups of high rank) and a state of the art survey of Geometric Iwasawa Theory explaining the recent proofs of various versions of the Main Conjecture, in the commutative and non-commutative settings.
This monograph contains many ideas on the analysis of survival data to present a comprehensive account of the field. The value of survival analysis is not confined to medical statistics, where the benefit of the analysis of data on such factors as life expectancy and duration of periods of freedom from symptoms of a disease as related to a treatment applied individual histories and so on, is obvious. The techniques also find important applications in industrial life testing and a range of subjects from physics to econometrics. In the eleven chapters of the book the methods and applications of are discussed and illustrated by examples.
A greatly expanded and heavily revised second edition, this popular guide provides instructions and clear examples for running analyses of variance (ANOVA) and several other related statistical tests of significance with SPSS. No other guide offers the program statements required for the more advanced tests in analysis of variance. All of the programs in the book can be run using any version of SPSS, including versions 11 and 11.5. A table at the end of the preface indicates where each type of analysis (e.g., simple comparisons) can be found for each type of design (e.g., mixed two-factor design). Providing comprehensive coverage of the basic and advanced topics in ANOVA, this is the only book available that provides extensive coverage of SPSS syntax, including the commands and subcommands that tell SPSS what to do, as well as the pull-down menu point-and-click method (PAC). Detailed explanation of the syntax, including what is necessary, desired, and optional helps ensure that users can validate the analysis being performed. The book features the output of each design along with a complete explanation of the related printout. The new edition was reorganized to provide all analysis related to one design type in the same chapter. It now features expanded coverage of analysis of covariance (ANCOVA) and mixed designs, new chapters on designs with random factors, multivariate designs, syntax used in PAC, and all new examples of output with complete explanations. The new edition is accompanied by downloadable resources with all of the book's data sets, as well as exercises for each chapter. This book is ideal for readers familiar with the basic concepts of the ANOVA technique including both practicing researchers and data analysts, as well as advanced students learning analysis of variance.
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