Rank-Based Methods for Shrinkage and Selection

This thoroughly revised and updated second edition of Methods for Community-Based Participatory Research for Health provides a step-by-step approach to the application of participatory approaches to quantitative and qualitative data collection and data analysis. With contributions from a distinguished panel of experts, this important volume shows how researchers, practitioners, and community partners can work together to establish and maintain equitable partnerships using a Community-Based Participatory Research (CBPR) approach to increase knowledge and improve the health and well-being of the communities involved. Written for students, practitioners, researchers, and community members, the book provides a comprehensive presentation of innovative partnership structures and processes, and covers the broad spectrum of methods needed to conduct CBPR in the widest range of research areas—including social determinants of health, health inequities, health promotion, community interventions, disease management, health services, and environmental health. The contributors examine effective methods used within the context of a CBPR approach including survey questionnaire, in-depth interview, focus group interview, ethnography, exposure assessment, and geographic information system mapping. In addition, each chapter describes a case study of the application of the method using a CBPR approach. The book also contains examples of concrete tools and measurement instruments that may be adapted by others involved in CBPR efforts.

Written by distinguished experts in the field, this book shows how researchers, practitioners, and community partners can work together to establish and maintain equitable partnerships using a Community-Based Participatory Research (CBPR) approach to increase knowledge and improve health and well-being of the communities involved. CBPR is a collaborative approach to research that draws on the full range of research designs, including case study, etiologic, longitudinal, experimental, and nonexperimental designs. CBPR data collection and analysis methods involve both quantitative and qualitative approaches. What distinguishes CBPR from other approaches to research is the active engagement of all partners in the process. This book provides a comprehensive and thorough presentation of CBPR study designs, specific data collection and analysis methods, and innovative partnership structures and process methods. This book informs students, practitioners, researchers, and community members about methods and applications needed to conduct CBPR in the widest range of research areas—including social determinants of health, health disparities, health promotion, community interventions, disease management, health services, and environmental health.

Praise for The Gamification of Learning and Instruction «Kapp argues convincingly that gamification is not just about adding points, levels and badges to an eLearning program, but about fundamentally rethinking learning design. He has put together a brilliant primer for learning professionals on how to gamify learning, packed with useful advice and examples.» —ANDERS GRONSTEDT, president, Gronstedt Group «After reading this book, you'll never be able to design boring learning again.» —CONNIE MALAMED, author, Visual Language For Designers; author/creator of The eLearning Coach Blog «Engaging, informative and complete; if you need to understand anything about instructional game design, this is the book you need. It provides the right amount of academic evidence, practical advice and insightful design tips to have you creating impactful learning in no time.» —SHERRY ENGEL, associate director learning technology, Penn Medicine Center for Innovation and Learning «What Karl Kapp has done with this book is looked at games and learning from every possible angle....he provocatively asks questions that the learning community needs to answer, like 'Do our design processes still work?' and 'Are we really meeting the needs of today's learners?' This book may make you anxious, make you laugh, or make you angry. But one thing it will definitely do is make you think.» —RICH MESCH, experiential learning guru, Performance Development Group

HIGHLIGHTS THE USE OF BAYESIAN STATISTICS TO GAIN INSIGHTS FROM EMPIRICAL DATA Featuring an accessible approach, Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems demonstrates how Bayesian statistics can help to provide insights into important issues facing business and management. The book draws on multidisciplinary applications and examples and utilizes the freely available software WinBUGS and R to illustrate the integration of Bayesian statistics within data-rich environments. Computational issues are discussed and integrated with coverage of linear models, sensitivity analysis, Markov Chain Monte Carlo (MCMC), and model comparison. In addition, more advanced models including hierarchal models, generalized linear models, and latent variable models are presented to further bridge the theory and application in real-world usage. Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems also features: Numerous real-world examples drawn from multiple management disciplines such as strategy, international business, accounting, and information systems An incremental skill-building presentation based on analyzing data sets with widely applicable models of increasing complexity An accessible treatment of Bayesian statistics that is integrated with a broad range of business and management issues and problems A practical problem-solving approach to illustrate how Bayesian statistics can help to provide insight into important issues facing business and management Bayesian Methods for Management and Business: Pragmatic Solutions for Real Problems is an important textbook for Bayesian statistics courses at the advanced MBA-level and also for business and management PhD candidates as a first course in methodology. In addition, the book is a useful resource for management scholars and practitioners as well as business academics and practitioners who seek to broaden their methodological skill sets.

This book is to be recommended as a standard shelf reference . . . and as a ‘must’ to be read by all who wish to better use and understand data involving dichotomous or dichotomizable measurements. —American Journal of Psychiatry In the two decades since the second edition of Statistical Methods for Rates and Proportions was published, evolving technologies and new methodologies have significantly changed the way today’s statistics are viewed and handled. The explosive development of personal computing and statistical software has facilitated the sophisticated analysis of data, putting capabilities that were once the domain of specialists into the hands of every researcher. The Third Edition of this important text addresses these changes and brings the literature up to date. While the previous edition focused on the use of desktop and handheld calculators, the new edition takes full advantage of modern computing power without losing the elegant simplicity that made the text so popular with students and practitioners alike. In authoritative yet clear terminology, the authors have brought the science of data analysis up to date without compromising its accessibility. Features of the Third Edition include: New material on sample size calculations and issues in clinical trials, and entirely new chapters on single-sample data, logistic regression, Poisson regression, regression models for matched samples, the analysis of correlated binary data, and methods for analyzing fourfold tables with missing data The addition of many new problems, both numerical and theoretical Answer sections for numerical problems and hints for tackling the theoretical ones A frequentist approach enhanced by the inclusion of empirical Bayesian methodology where appropriate Combining the latest research with the original studies that established the previous editions as leaders in the field, Statistical Methods for Rates and Proportions, Third Edition will continue to be an invaluable resource for students, statisticians, biostatisticians, and epidemiologists.

Quantitative Methods for Finance and Investments ensures that readers come away from reading it with a reasonable degree of comfort and proficiency in applying elementary mathematics to several types of financial analysis. All of the methodology in this book is geared toward the development, implementation, and analysis of financial models to solve financial problems.

This book aims to stimulate and promote the wide-ranging aspects of green chemistry and its major role in ensuring sustainable development. The book covers the following areas: green chemistry; green reagents and atom economy; safeguarding the atmosphere; industrial green catalysis; alternative reaction conditions; biocatalysis and green chemistry. This book is based on the third edition of the Collection of Lectures of the Summer Schools on Green Chemistry held in Venice, Italy in the summers of 1998-2003 (sponsored by the European Commission, TMR and Improving Programmes and carried out by the Consortzio Interuniversitario La Chemica per l'Ambiente).

Reliability is one of the most important attributes for the products and processes of any company or organization. This important work provides a powerful framework of domain-independent reliability improvement and risk reducing methods which can greatly lower risk in any area of human activity. It reviews existing methods for risk reduction that can be classified as domain-independent and introduces the following new domain-independent reliability improvement and risk reduction methods: Separation Stochastic separation Introducing deliberate weaknesses Segmentation Self-reinforcement Inversion Reducing the rate of accumulation of damage Permutation Substitution Limiting the space and time exposure Comparative reliability models The domain-independent methods for reliability improvement and risk reduction do not depend on the availability of past failure data, domain-specific expertise or knowledge of the failure mechanisms underlying the failure modes. Through numerous examples and case studies, this invaluable guide shows that many of the new domain-independent methods improve reliability at no extra cost or at a low cost. Using the proven methods in this book, any company and organisation can greatly enhance the reliability of its products and operations.

Mathematical Methods for Physical and Analytical Chemistry presents mathematical and statistical methods to students of chemistry at the intermediate, post-calculus level. The content includes a review of general calculus; a review of numerical techniques often omitted from calculus courses, such as cubic splines and Newton’s method; a detailed treatment of statistical methods for experimental data analysis; complex numbers; extrapolation; linear algebra; and differential equations. With numerous example problems and helpful anecdotes, this text gives chemistry students the mathematical knowledge they need to understand the analytical and physical chemistry professional literature.