Broadening its scope to nonstatisticians, Bayesian Methods for Data Analysis, Third Edition provides an accessible introduction to the foundations and applications of Bayesian analysis. Along with a complete reorganization of the material, this edition concentrates more on hierarchical Bayesian modeling as implemented via Markov chain Monte Carlo (MCMC) methods and related data analytic techniques. New to the Third Edition New data examples, corresponding R and WinBUGS code, and homework problems Explicit descriptions and illustrations of hierarchical modeling—now commonplace in Bayesian data analysis A new chapter on Bayesian design that emphasizes Bayesian clinical trials A completely revised and expanded section on ranking and histogram estimation A new case study on infectious disease modeling and the 1918 flu epidemic A solutions manual for qualifying instructors that contains solutions, computer code, and associated output for every homework problem—available both electronically and in print Ideal for Anyone Performing Statistical Analyses Focusing on applications from biostatistics, epidemiology, and medicine, this text builds on the popularity of its predecessors by making it suitable for even more practitioners and students.
Simple, clear explanations of twenty ways in which mathematics helps us to understand practical issues of everyday life. Suitable for teenagers and adults, and beautifully produced. Highly recommended!" - Professor Ian Stewart, bestselling author of The Cabinet of Mathematical Curiosities Mathematics is an indispensable tool for life. From the systems that underpin our newsfeeds, through to the data analysis that informs our health and financial decisions, to the algorithms that power how we search online – mathematics is at the heart of how our modern world functions. In 20 dip-in lessons, Understanding Numbers explains how and why mathematics fuels your world and arms you with the knowledge to make wiser choices in all areas of your life. • Make sense of health statistics • Understand the mathematics behind political voting systems • Get to grips with how online search tools work • Discover how mathematics can create the perfect city
Univariate and multivariate multilevel models are used to understand how to design studies and analyze data in this comprehensive text distinguished by its variety of applications from the educational, behavioral, and social sciences. Basic and advanced models are developed from the multilevel regression (MLM) and latent variable (SEM) traditions within one unified analytic framework for investigating hierarchical data. The authors provide examples using each modeling approach and also explore situations where alternative approaches may be more appropriate, given the research goals. Numerous examples and exercises allow readers to test their understanding of the techniques presented. Changes to the new edition include: -The use of Mplus 7.2 for running the analyses including the input and data files at www.routledge.com/9781848725522. -Expanded discussion of MLM and SEM model-building that outlines the steps taken in the process, the relevant Mplus syntax, and tips on how to evaluate the models. -Expanded pedagogical program now with chapter objectives, boldfaced key terms, a glossary, and more tables and graphs to help students better understand key concepts and techniques. -Numerous, varied examples developed throughout which make this book appropriate for use in education, psychology, business, sociology, and the health sciences. -Expanded coverage of missing data problems in MLM using ML estimation and multiple imputation to provide currently-accepted solutions (Ch. 10). -New chapter on three-level univariate and multilevel multivariate MLM models provides greater options for investigating more complex theoretical relationships(Ch.4). -New chapter on MLM and SEM models with categorical outcomes facilitates the specification of multilevel models with observed and latent outcomes (Ch.8). -New chapter on multilevel and longitudinal mixture models provides readers with options for identifying emergent groups in hierarchical data (Ch.9). -New chapter on the utilization of sample weights, power analysis, and missing data provides guidance on technical issues of increasing concern for research publication (Ch.10). Ideal as a text for graduate courses on multilevel, longitudinal, latent variable modeling, multivariate statistics, or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this book’s practical approach also appeals to researchers. Recommended prerequisites are introductory univariate and multivariate statistics.
Bayesian networks and decision graphs are formal graphical languages for representation and communication of decision scenarios requiring reasoning under uncertainty. Their strengths are two-sided. It is easy for humans to construct and understand them, and when communicated to a computer, they can easily be compiled. The book emphasizes both the human and the computer side. It gives a thorough introduction to Bayesian networks, decision trees and influence diagrams as well as algorithms and complexity issues.
This book provides an introduction to the use of statistical concepts and methods to model and analyze financial data. The ten chapters of the book fall naturally into three sections. Chapters 1 to 3 cover some basic concepts of finance, focusing on the properties of returns on an asset. Chapters 4 through 6 cover aspects of portfolio theory and the methods of estimation needed to implement that theory. The remainder of the book, Chapters 7 through 10, discusses several models for financial data, along with the implications of those models for portfolio theory and for understanding the properties of return data. The audience for the book is students majoring in Statistics and Economics as well as in quantitative fields such as Mathematics and Engineering. Readers are assumed to have some background in statistical methods along with courses in multivariate calculus and linear algebra.
Learn How to Properly Analyze Categorical Data Analysis of Categorical Data with R presents a modern account of categorical data analysis using the popular R software. It covers recent techniques of model building and assessment for binary, multicategory, and count response variables and discusses fundamentals, such as odds ratio and probability estimation. The authors give detailed advice and guidelines on which procedures to use and why to use them. The Use of R as Both a Data Analysis Method and a Learning Tool Requiring no prior experience with R, the text offers an introduction to the essential features and functions of R. It incorporates numerous examples from medicine, psychology, sports, ecology, and other areas, along with extensive R code and output. The authors use data simulation in R to help readers understand the underlying assumptions of a procedure and then to evaluate the procedure’s performance. They also present many graphical demonstrations of the features and properties of various analysis methods. Web Resource The data sets and R programs from each example are available at www.chrisbilder.com/categorical. The programs include code used to create every plot and piece of output. Many of these programs contain code to demonstrate additional features or to perform more detailed analyses than what is in the text. Designed to be used in tandem with the book, the website also uniquely provides videos of the authors teaching a course on the subject. These videos include live, in-class recordings, which instructors may find useful in a blended or flipped classroom setting. The videos are also suitable as a substitute for a short course.
Cancers in the Urban Environment: How Malignant Diseases Are Caused and Distributed among the Diverse People and Neighborhoods of a Major Global Metropolis, Second Edition, provides a detailed description of the occurrence of common forms of cancer in the ethnically, socially and environmentally complex milieu of a modern urban complex. The location is Los Angeles County, and the patterns of 72 different malignancies are described according to race, age, sex, social class calendar time (since 1972) and most notably, individual neighborhood, using detailed maps of high risk. This second edition uses twice as many cases and more demographic diversity. Physicians and scientific investigators in California and elsewhere can use the material provided to counsel patients and evaluate the consistency of any specific pattern of occurrence with each specific causal hypothesis. A detailed appendix describes the source of data, provides the basis for the choices made in the production of the volume, and gives a perspective on the search for "clusters" of malignancy. - Compares different types of cancers with respect to the degree of non-random occurrence - Contains numerous maps detailing the demographic and geographic pattern of cancer occurrence in Los Angeles County - Provides an empirical perspective on the search for disease "clusters
This book looks at the foundations of school self-evaluation from a scientific as from a practical perspective. Planning concepts, restructuring of education systems, organizational theory on schools, evaluation methodology and models of school effectiveness and school improvement are discussed as contributing to the overall conceptualization of school self-evaluation. A broad range of approaches is presented and methodological requirements are discussed. School self-evaluation contains controversial issues that reflect tension between the need for objectivity in a context that is permeated by values and potential conflicts of interests. Similar tensions may be seen to exist with respect to the static and "reductionist" aspects of available data collection procedures in a complex and dynamic situation and the appeal for external accountability on the one hand and improvement oriented self-refection on the other. The mission of the book is to clarify these tensions and offer ways to deal with them in practical applications. The school effectiveness knowledge base is offered as a substantive educational frame of references that serves an important function in selecting relevant factors for data collection and the use of the evaluation results.
Numericon tells the stories of the numbers, mathematical discoveries, oddities and personalities that have shaped the way we understand the world around us. Each chapter is its own story about a number: why 12 is a sublime number, why 13 is unlucky and 7 lucky, and how imaginary numbers hold up buildings. The book tells the stories of ancient mathematicians, ground-breaking discoveries and mathematical applications that affect our world and our lives in so many ways.
The authoritative guide for Data Monitoring Committees—fully revised and updated The number of clinical trials sponsored by government agencies and pharmaceutical companies has grown in recent years, prompting an increased need for interim monitoring of data on safety and efficacy. Data Monitoring Committees (DMCs) are an essential component of many clinical trials, safeguarding trial participants and protecting the credibility and validity of the study. Data Monitoring Committees in Clinical Trials: A Practical Perspective, 2nd Edition offers practical advice for those managing and conducting clinical trials and serving on Data Monitoring Committees, providing a practical overview of the establishment, purpose, and responsibilities of these committees. Examination of topics such as the composition and independence of DMCs, statistical, philosophical and ethical considerations, and determining when a DMC is needed, presents readers with a comprehensive foundational knowledge of clinical trial oversight. Providing recent examples to illustrate DMC principles, this fully-updated guide reflects current developments and practices in clinical trial oversight and offers expanded coverage of emerging issues and challenges in the field. This new second edition covers the most current information on DMC policies, issues in monitoring trials using new designs, and recent trial publications relevant to DMC decision-making. • Presents practical advice for those managing and conducting clinical trials and serving on Data Monitoring Committees • Illustrates the types of challenging issues Data Monitoring Committees face in practical situations • Provides updated and expanded coverage of topics including regulatory and funding agency guidelines and trial designs and their associated demands and limitations • Includes a new chapter addressing legal issues that affect DMC members and discusses general litigation concerns relevant to clinical research • Expands treatment of current journal publications addressing DMC issues Data Monitoring Committees in Clinical Trials: A Practical Perspective, 2nd Edition is a must-have text for anyone engaged in DMC activities as well as trial sponsors, clinical trial researchers, regulatory and bioethics professionals, and those associated with clinical trials in academic, government and industry settings.
Hurricanes are nature's most destructive storms and they are becoming more powerful as the globe warms. Hurricane Climatology explains how to analyze and model hurricane data to better understand and predict present and future hurricane activity. It uses the open-source and now widely used R software for statistical computing to create a tutorial-style manual for independent study, review, and reference. The text is written around the code that when copied will reproduce the graphs, tables, and maps. The approach is different from other books that use R. It focuses on a single topic and explains how to make use of R to better understand the topic. The book is organized into two parts, the first of which provides material on software, statistics, and data. The second part presents methods and models used in hurricane climate research.
This volume ... includes hundreds of photographs, many of them never before published. The authors provide text and commentary, organizing the photographs into chapters covering the origins of war, its conventional and guerrilla phases, the war on the rivers, medicine ... the experiences of Missourians who served out of state, and the process of reunion in the postwar years"--Fly leaf.
A Financial Times Book of the Year. A clear, readable analysis of the inescapable fact that Generation Y (and subsequent generations) will be poorer than their parents, and how we should pursue other economic paths. If you are part of the 99% – and there is a 99% chance that you are – then you are one of the first generation in living memory who can expect to be poorer than your parents, even as the economy continues to grow. And you could be quite a lot poorer. If we continue as we are going, the civilisation we enjoy today will not last until 2050. Buying their own house is a distant dream for most young people; their wages are failing to keep pace with inflation; and more and more people are having to rely on food banks. Our age is one of chronic anxiety. If the economy is doing so well, how can most people not be doing well? If the pie is growing, why aren't we all getting bigger slices? This book shows what we, the 99%, can do to end mass impoverishment and build a society worth living in: an age of abundance, in which everyone benefits.
Where does hunch end and evidence begin? Too much is written and said about school improvement - about improvements in teaching and learning - with far too little attention to this question. This book provides vivid discussion from distinguished protagonists and antagonists about what gets called 'evidence-based practice'. Reading it, all involved in education - policymakers and practitioners alike - can proceed more confidently."- Professor Tim Brighouse, London Schools Commissioner The movement to evidence-based practice in education is as important as it is controversial, and this book explores the arguments of leading advocates and critics. The book begins with an explication of evidence-based practice. Some of the ideas of its proponents are discussed, including the Campbell Collaboration, and the application to education of Cochrane-style reviews and meta-analyses. The thinking behind evidence based practice has been the subject of much criticism, particularly in education, and this criticism is aired in the second part of the book. Questions have been raised about what we mean by evidence, about how particular kinds of evidence may be privileged over other kinds of evidence, about the transferability of research findings to practice, and about the consequences of a move to evidence-based practice for governance in education. Given that the origins of the interest in evidence-based practice come largely from its use in medicine, questions arise about the validity of the transposition, and contributors to the third part of the book address this transposition. The issues raised in the book, while primarily those raised by educators, are of relevance also to professionals in medicine, social work and psychology.
This book is a very useful text for anyone studying comparative education systems as well as those who seek to understand more fully the complexities and frustrations that lie beneath the underuse of the leadership skills and talents of women in schools, colleges and higher education in a number of European contexts: England and Wales, France, The Federal Republic of Germany, Greece, Hungary, Ireland, Italy, The Netherlands, Norway and Spain' - "School Leadership & Management " There are few books of which one can say 'all secondary teachers and governors should read this book' but this is one of them. I would recommend it to primary colleagues too....Its messages about school effectiveness can uniquely be applied to school improvement because there is data about how the same children fared under different regimes in different subject areas in the same school' - "School Leadership & Management " This major new school effectiveness study is a thought-provoking investigation of the concept of secondary school effectiveness. Based on a three-year study of secondary schools GCSE performance, the authors point to the importance of looking at: trends over time; effectiveness for different groups of students; and subject differences. They highlight the importance of moving beyond league table approaches and the need to focus on individual departments using value-added approaches. Forging Links illustrates the complexities of judging school performance. The findings make a significant contribution to our understanding of the factors and processes which help some schools and departments to enhance student progres
In the first part, this book analyzes the knowledge discovery process in order to understand the relations between knowledge discovery steps and focusing. The part devoted to the development of focusing solutions opens with an analysis of the state of the art, then introduces the relevant techniques, and finally culminates in implementing a unified approach as a generic sampling algorithm, which is then integrated into a commercial data mining system. The last part evaluates specific focusing solutions in various application domains. The book provides various appendicies enhancing easy accessibility. The book presents a comprehensive introduction to focusing in the context of data mining and knowledge discovery. It is written for researchers and advanced students, as well as for professionals applying data mining and knowledge discovery techniques in practice.
This balanced and well-integrated text gives a lucid overview of the entire process of genetic epidemiology, from familial aggregation through segregation, likage, and association studies. It is illustrated throughout with examples from the literature on cancer genetics. Statistical concepts are developed in depth, but with a focus on applications. Introductory chapters on molecular biology, Mendelian genetics, epidemiology, statistics, and population genetics are included. Oriented to graduate students in biostatistics, epidemiology, and human genetics, the book will also be a useful reference for researchers. It gives equal emphasis to study designs and data analysis.
Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors’ collective experiences in this field, Introduction to Statistical Methods for Clinical Trials presents various statistical topics relevant to the design, monitoring, and analysis of a clinical trial. After reviewing the history, ethics, protocol, and regulatory issues of clinical trials, the book provides guidelines for formulating primary and secondary questions and translating clinical questions into statistical ones. It examines designs used in clinical trials, presents methods for determining sample size, and introduces constrained randomization procedures. The authors also discuss how various types of data must be collected to answer key questions in a trial. In addition, they explore common analysis methods, describe statistical methods that determine what an emerging trend represents, and present issues that arise in the analysis of data. The book concludes with suggestions for reporting trial results that are consistent with universal guidelines recommended by medical journals. Developed from a course taught at the University of Wisconsin for the past 25 years, this textbook provides a solid understanding of the statistical approaches used in the design, conduct, and analysis of clinical trials.
A systematic treatment of the statistical challenges that arise in environmental health studies and the use epidemiologic data in formulating public policy, at a level suitable for graduate students and epidemiologic researchers.
High-stakes public examinations exert a dominant influence in most education systems. They affect both teacher and student behavior, especially at the middle and upper levels of secondary education. The content of past examinations tends to dictate what is taught and how it is taught and, more important, what is learned and how it is learned. By changing aspects of these examinations, especially their content and format, education systems can have a strong positive impact on teacher behavior and student learning, help raise student achievement levels, and better prepare students for tertiary-level education and for employment. Examination agencies, many of which have followed the same procedures over decades, can learn from the successes and failures of other systems. This book addresses current issues related to the development, administration, scoring, and usage of these high-stakes public examinations, identifying key issues and problems related to examinations in many emerging market economies as well as in advanced economies. The book’s primary audience consists of public examination officials on national, regional, and state examination boards, but the book should also be of interest to senior education policy makers concerned with certification and learning achievement standards, to academics and researchers interested in educational assessment, to governmental and education agencies responsible for student selection, and to professionals at development organizations. “This extremely well-written and comprehensive book offers a timely review of the diversity of public examination practices worldwide; of the tensions between examinations and learning; and of the technical expertise involved in the creation of valid, reliable, and fair assessments. It reminds us that as “the diploma disease†? takes hold with an ever-greater intensity at every stage of education worldwide, and the commercial business of testing flourishes, those concerned with educational quality and meaningful learning must be on guard to prevent the assessment tail wagging the educational dog.†? Angela W. Little, Professor Emerita, Institute of Education, University College London “This book is very well structured and written and draws on the authors’ remarkable global knowledge across countries and histories. It will be a great asset both to administrators responsible for examinations and to academics and other professionals who seek to understand the nature and impact of examinations of different types and in different settings.†? Mark Bray, UNESCO Chair Professor of Comparative Education, University of Hong Kong; and former Director, UNESCO International Institute for Educational Planning “I am sure that Public Examinations Examined, which thoroughly analyzes the practice of public examinations in different countries and makes profound and well-grounded conclusions, will arouse very great interest and will serve to further improve public examinations.†? Victor Bolotov, Distinguished Professor, Higher School of Economics, National Research University, Moscow; member, Russian Academy of Education; and former Deputy Minister of Education, Russian Federation
This is the only book that teaches all aspects of modern mathematical modeling and that is specifically designed to introduce undergraduate students to problem solving in the context of biology. Included is an integrated package of theoretical modeling and analysis tools, computational modeling techniques, and parameter estimation and model validation methods, with a focus on integrating analytical and computational tools in the modeling of biological processes. Divided into three parts, it covers basic analytical modeling techniques; introduces computational tools used in the modeling of biological problems; and includes various problems from epidemiology, ecology, and physiology. All chapters include realistic biological examples, including many exercises related to biological questions. In addition, 25 open-ended research projects are provided, suitable for students. An accompanying Web site contains solutions and a tutorial for the implementation of the computational modeling techniques. Calculations can be done in modern computing languages such as Maple, Mathematica, and MATLAB?.
Now in its second edition, this textbook provides an applied and unified introduction to parametric, nonparametric and semiparametric regression that closes the gap between theory and application. The most important models and methods in regression are presented on a solid formal basis, and their appropriate application is shown through numerous examples and case studies. The most important definitions and statements are concisely summarized in boxes, and the underlying data sets and code are available online on the book’s dedicated website. Availability of (user-friendly) software has been a major criterion for the methods selected and presented. The chapters address the classical linear model and its extensions, generalized linear models, categorical regression models, mixed models, nonparametric regression, structured additive regression, quantile regression and distributional regression models. Two appendices describe the required matrix algebra, as well as elements of probability calculus and statistical inference. In this substantially revised and updated new edition the overview on regression models has been extended, and now includes the relation between regression models and machine learning, additional details on statistical inference in structured additive regression models have been added and a completely reworked chapter augments the presentation of quantile regression with a comprehensive introduction to distributional regression models. Regularization approaches are now more extensively discussed in most chapters of the book. The book primarily targets an audience that includes students, teachers and practitioners in social, economic, and life sciences, as well as students and teachers in statistics programs, and mathematicians and computer scientists with interests in statistical modeling and data analysis. It is written at an intermediate mathematical level and assumes only knowledge of basic probability, calculus, matrix algebra and statistics.
Multilevel modelling is a data analysis method that is frequently used to investigate hierarchal data structures in educational, behavioural, health, and social sciences disciplines. Multilevel data analysis exploits data structures that cannot be adequately investigated using single-level analytic methods such as multiple regression, path analysis, and structural modelling. This text offers a comprehensive treatment of multilevel models for univariate and multivariate outcomes. It explores their similarities and differences and demonstrates why one model may be more appropriate than another, given the research objectives. New to this edition: An expanded focus on the nature of different types of multilevel data structures (e.g., cross-sectional, longitudinal, cross-classified, etc.) for addressing specific research goals; Varied modelling methods for examining longitudinal data including random-effect and fixed-effect approaches; Expanded coverage illustrating different model-building sequences and how to use results to identify possible model improvements; An expanded set of applied examples used throughout the text; Use of four different software packages (i.e., Mplus, R, SPSS, Stata), with selected examples of model-building input files included in the chapter appendices and a more complete set of files available online. This is an ideal text for graduate courses on multilevel, longitudinal, latent variable modelling, multivariate statistics, or advanced quantitative techniques taught in psychology, business, education, health, and sociology. Recommended prerequisites are introductory univariate and multivariate statistics.
Starting your research project can feel daunting, but this best-selling project guide has your back! Now in its fourth edition, the book provides easy to follow advice to navigate every step of your research project, from choosing your research question, deciding on your research design and methodology, collecting and analysing your data, and writing up your finished project. Presenting a clear and detailed roadmap to ensure you don’t miss a step, the book includes: • Case studies and real-life examples from a range of disciplines so you can learn from other researchers who have been in your shoes • DIY activities so you can practise your skills and get to grips with key concepts • Practical advice on how to organise your writing, develop your flow and build strong arguments • Further guidance on assessing ethical risk, including examples of high, medium, and low risk projects Written in Gary’s signature straightforward style, this book is an essential companion for anyone undertaking a research project in the applied social sciences.
Proceedings of the AMS-IMS-SIAM Joint Summer Research Conference Held June 21-27, 1990, with Support from the National Science Foundation, the National Security Agency, and the Office of Naval Research
Proceedings of the AMS-IMS-SIAM Joint Summer Research Conference Held June 21-27, 1990, with Support from the National Science Foundation, the National Security Agency, and the Office of Naval Research
This volume contains the proceedings of the MS-IMS-SIAM Joint Summer Research Conference on Strategies for Sequential Search and Selection in Real Time, held in June 1990 at the University of Massachusetts at Amherst. The conference focused on problems related to sequential observation of random variables and selection of actions in real time. This book will provide readers with a feeling for the breadth and depth of contemporary research in these areas.
This text provides a state-of-the-art treatment of distributional regression, accompanied by real-world examples from diverse areas of application. Maximum likelihood, Bayesian and machine learning approaches are covered in-depth and contrasted, providing an integrated perspective on GAMLSS for researchers in statistics and other data-rich fields.
Modern Directional Statistics collects important advances in methodology and theory for directional statistics over the last two decades. It provides a detailed overview and analysis of recent results that can help both researchers and practitioners. Knowledge of multivariate statistics eases the reading but is not mandatory. The field of directional statistics has received a lot of attention over the past two decades, due to new demands from domains such as life sciences or machine learning, to the availability of massive data sets requiring adapted statistical techniques, and to technological advances. This book covers important progresses in distribution theory,high-dimensional statistics, kernel density estimation, efficient inference on directional supports, and computational and graphical methods. Christophe Ley is professor of mathematical statistics at Ghent University. His research interests include semi-parametrically efficient inference, flexible modeling, directional statistics and the study of asymptotic approximations via Stein’s Method. His achievements include the Marie-Jeanne Laurent-Duhamel prize of the Société Française de Statistique and an elected membership at the International Statistical Institute. He is associate editor for the journals Computational Statistics & Data Analysis and Econometrics and Statistics. Thomas Verdebout is professor of mathematical statistics at Université libre de Bruxelles (ULB). His main research interests are semi-parametric statistics, high- dimensional statistics, directional statistics and rank-based procedures. He has won an annual prize of the Belgian Academy of Sciences and is an elected member of the International Statistical Institute. He is associate editor for the journals Statistics and Probability Letters and Journal of Multivariate Analysis.
This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers. New to this revised and expanded edition: • An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples • A new comparison of plug-in prediction methodologies for real-valued simulator output • An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions • A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization • A new chapter describing graphical and numerical sensitivity analysis tools • Substantial new material on calibration-based prediction and inference for calibration parameters • Lists of software that can be used to fit models discussed in the book to aid practitioners
This volume presents a comprehensive and comprehensible set of guidelines for reporting the statistical analyses and research designs and activities commonly used in biomedical research.
Data can be extremely valuable if we are able to extract information from them. This is why multivariate data analysis is essential for business and science. This book offers an easy-to-understand introduction to the most relevant methods of multivariate data analysis. It is strictly application-oriented, requires little knowledge of mathematics and statistics, demonstrates the procedures with numerical examples and illustrates each method via a case study solved with IBM’s statistical software package SPSS. Extensions of the methods and links to other procedures are discussed and recommendations for application are given. An introductory chapter presents the basic ideas of the multivariate methods covered in the book and refreshes statistical basics which are relevant to all methods. For the 2nd edition, all chapters were checked and calculated using the current version of IBM SPSS. Contents Introduction to empirical data analysis Regression analysis Analysis of variance Discriminant analysis Logistic regression Contingency analysis Factor analysis Cluster analysis Conjoint analysis The original German version is now available in its 17th edition. In 2015, this book was honored by the Federal Association of German Market and Social Researchers as “the textbook that has shaped market research and practice in German-speaking countries”. A Chinese version is available in its 3rd edition. On the website www.multivariate-methods.info, the authors further analyze the data with Excel and R and provide additional material to facilitate the understanding of the different multivariate methods. In addition, interactive flashcards are available to the reader for reviewing selected focal points. Download the Springer Nature Flashcards App and use exclusive content to test your knowledge.
This book gives a unifying framework for estimating the abundance of open populations: populations subject to births, deaths and movement, given imperfect measurements or samples of the populations. The focus is primarily on populations of vertebrates for which dynamics are typically modelled within the framework of an annual cycle, and for which stochastic variability in the demographic processes is usually modest. Discrete-time models are developed in which animals can be assigned to discrete states such as age class, gender, maturity, population (within a metapopulation), or species (for multi-species models). The book goes well beyond estimation of abundance, allowing inference on underlying population processes such as birth or recruitment, survival and movement. This requires the formulation and fitting of population dynamics models. The resulting fitted models yield both estimates of abundance and estimates of parameters characterizing the underlying processes.
The most comprehensive, multi-disciplinary text in the field, Cummings Otolaryngology: Head and Neck Surgery, 7th Edition, provides detailed, practical answers and easily accessible clinical content on the complex issues that arise for otolaryngologists at all levels, across all subspecialties. This award-winning text is a one-stop reference for all stages of your career—from residency and board certification through the challenges faced in daily clinical practice. Updated content, new otology editor Dr. Howard W. Francis, and new chapters and videos ensure that this 7th Edition remains the definitive reference in today's otolaryngology. - Brings you up to date with the latest minimally invasive procedures, recent changes in rhinology, and new techniques and technologies that are shaping patient outcomes. - Contains 12 new chapters, including Chronic Rhinosinusitis, Facial Pain, Geriatric Otology, Middle Ear Endoscopic Surgery, Pediatric Speech Disorders, Pediatric Cochlear Implantation, Tongue-Ties and Lip Ties, Laryngotracheal Clefts, and more. - Covers recent advances and new approaches such as the Draf III procedure for CRS affecting the frontal recess, endoscopic vidian and posterior nasal neurectomy for non-allergic rhinitis, and endoscopic approaches for sinonasal and orbital tumors, both extra- and intraconal. - Provides access to 70 key indicator (Accreditation Council for Graduate Medical Education Key Indicator Procedures), and surgical videos – an increase of 43% over the previous edition. - Offers outstanding visual support with 4,000 high-quality images and hundreds of quick-reference tables and boxes. - Enhanced eBook version included with purchase. Your enhanced eBook allows you to access all of the text, figures, and references from the book on a variety of devices.
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.
Ideal for experienced students and researchers in the social sciences who wish to refresh or extend their understanding of statistics, and to apply advanced statistical procedures using SPSS or R. Key theory is reviewed and illustrated with examples of how to apply these concepts using real data.
Heart disease is currently the leading cause of maternal mortality in developed countries and is expected to increase further due to advanced maternal age and conditions such as type 2 diabetes. Maternal Cardiac Care: A Guide to Managing Pregnant Women with Heart Disease is an up-to-date, multidisciplinary resource for physicians and advanced practice nurses caring for pregnant patients with a variety of preexisting and emerging cardiac issues. - Offers comprehensive information on caring for women with heart disease, in an easy-to-follow, quick-access format. - Shares knowledge from a multidisciplinary group of experts who are well versed in the team approach needed to treat this high-risk patient population. - Includes extensive references for readers who want to delve more deeply into specific subjects. - Ideal for obstetricians, internists, cardiologists, critical care specialists, and advanced practice nurses involved in caring for pregnant patients, as well as institutions and departments that need detailed guidance on establishing a maternal cardiac care program.
Through four editions, Cummings Otolaryngology has been the world's most trusted source for comprehensive guidance on all facets of head and neck surgery. This 5th Edition - edited by Paul W. Flint, Bruce H. Haughey, Valerie J. Lund, John K. Niparko, Mark A. Richardson, K. Thomas Robbins, and J. Regan Thomas – equips you to implement all the newest discoveries, techniques, and technologies that are shaping patient outcomes. You'll find new chapters on benign neoplasms, endoscopic DCR, head and neck ultrasound, and trends in surgical technology... a new section on rhinology... and coverage of hot topics such as Botox. Plus, your purchase includes access to the complete contents of this encyclopedic reference online, with video clips of key index cases! Overcome virtually any clinical challenge with detailed, expert coverage of every area of head and neck surgery, authored by hundreds of leading luminaries in the field. See clinical problems as they present in practice with 3,200 images - many new to this edition. Consult the complete contents of this encyclopedic reference online, with video clips of key index cases! Stay current with new chapters on benign neoplasms, endoscopic DCR, head and neck ultrasound, and trends in surgical technology... a new section on rhinology... and coverage of hot topics including Botox. Get fresh perspectives from a new editorial board and many new contributors. Find what you need faster through a streamlined format, reorganized chapters, and a color design that expedites reference.
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