Statistical and Methodological Aspects of Oral Health Research provides oral health researchers with an overview of the methodological aspects that are important in planning, conducting and analyzing their research projects whilst also providing biostatisticians with an idea of the statistical problems that arise when tackling oral health research questions. This collection presents critical reflections on oral health research and offers advice on practical aspects of setting up research whilst introducing the reader to basic as well as advanced statistical methodology. Features: An introduction to research methodology and an exposition of the state of the art. A variety of examples from oral health research. Contributions from well-known oral health researchers, epidemiologists and biostatisticians, all of whom have rich experience in this area. Recent developments in statistical methodology prompted by a variety of dental applications. Presenting both an introduction to research methodology and an exposition of the latest advances in oral health research, this book will appeal both beginning and experienced oral health researchers as well as biostatisticians and epidemiologists.

Clinical Research in Oral Health surveys the essentials of clinical research in oral health, anchoring these principles within the specific context of the oral health arena. Addressing research questions exclusively applicable to dentistry and oral health, the book thoroughly illustrates the principles and practice of oral health clinical research. Clinical Research in Oral Health also clarifies the framework of regulatory issues and presents emerging concepts in clinical translation, relating the research principles to clinical improvement.

Learn about the challenges, current trends, and the positive role that you can play in improving the dental health of the community. Completely revised and updated by members of the American Association of Public Health Dentistry, Burt and Eklund's Dentistry, Dental Practice, and the Community, 7th Edition presents dentistry and dental practice against the ever-changing backdrop of economic, technological, and demographic trends, as well as the distribution of the oral diseases that dental professionals treat and prevent. Readers will learn the latest techniques of research and measurement, and how oral disease may be limited through control and prevention. This updated text also addresses the new educational competencies for predoctoral/ post-doctoral dental students and dental hygiene students with updated and new content on cultural competency, oral health literacy, social responsibility, motivational interviewing, and oral systemic associations. All in all, this text takes a comprehensive look at the social context of dental care and the difference you can make in improving the health of the community you serve. - Logical four-part organization divides content into dentistry and the community; dental care delivery; methods and measurement of oral diseases and conditions; and health promotion and prevention of oral diseases. - A focus on need-to-know content emphasizes the important core information while providing comprehensive coverage of dental public health. - Comprehensive analysis of dentistry's social and professional role examines issues such as epidemiology of oral diseases, prevention, and the provision of care. - Evidence-based recommendations reflect the latest literature on today's public health issues. - Illustrations, tables, and graphics illustrate the key material and visually enhance discussions. - NEW! Completely revised and updated content looks at populations oral health and dental care as well as how it fits into a changing world. - NEW! Coverage of new educational competencies provides predoctoral/ post-doctoral dental students and dental hygiene students with updated and new content on cultural competency, oral health literacy, social responsibility, motivational interviewing, and oral systemic associations. - NEW! New chapters cover the applications of epidemiology and biostatistics in dental public health, oral health as it related to quality of life, oral health education, health literacy, social determinants of health and health disparities, and delivery of oral healthcare in Canada. - NEW! Newly revised competencies for the Dental Public Health specialty are incorporated throughout the book.

"Basic oral health surveys provide a sound basis for assessing the current oral health status of a population and its future needs for oral health care. The World Health Organization (WHO) has a long tradition of epidemiological survey methodology, which includes a description of the diagnostic criteria that can be readily understood and applied in public health programmes worldwide. The WHO manual Oral Health Surveys - Basic Methods has encouraged countries to conduct standardized oral health surveys that are comparable internationally. The WHO Global Oral Health Data Bank collates the data gathered through country surveys on the burden of oral disease and WHO recommended statistical analysis on key indicator age groups of children and adults. This manual aims to encourage national oral health survey planners to standardize measurements of oral diseases and conditions that are important for planning and evaluation of oral health programmes, as well as to ensure the comparability of data collected in a wide range of environments. It does this by applying the WHO global approach to chronic disease surveillance to an operational model for integration of oral health into chronic disease surveillance systems."--Publisher's description.

The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monitoring the effect of intervening in some environmental system. This book provides an overview of modern statistical techniques that may be relevant in problems of this nature. Practitioners studying environmental change will be familiar with many classical statistical procedures for the detection and estimation of trends. However, the ever increasing capacity to collect and process vast amounts of environmental information has led to growing awareness that such procedures are limited in the insights that they can deliver. At the same time, significant developments in statistical methodology have often been widely dispersed in the statistical literature and have therefore received limited exposure in the environmental science community. This book aims to provide a thorough but accessible review of these developments. It is split into two parts: the first provides an introduction to this area and the second part presents a collection of case studies illustrating the practical application of modern statistical approaches to the analysis of trends in real studies. Key Features: Presents a thorough introduction to the practical application and methodology of trend analysis in environmental science. Explores non-parametric estimation and testing as well as parametric techniques. Methods are illustrated using case studies from a variety of environmental application areas. Looks at trends in all aspects of a process including mean, percentiles and extremes. Supported by an accompanying website featuring datasets and R code. The book is designed to be accessible to readers with some basic statistical training, but also contains sufficient detail to serve as a reference for practising statisticians. It will therefore be of use to postgraduate students and researchers both in the environmental sciences and in statistics.

This book gives professionals in clinical research valuable information on the challenging issues of the design, execution, and management of clinical trials, and how to resolve these issues effectively. It also provides understanding and practical guidance on the application of contemporary statistical methods to contemporary issues in safety evaluation during medical product development. Each chapter provides sufficient detail to the reader to undertake the design and analysis of experiments at various stages of product development, including comprehensive references to the relevant literature. Provides a guide to statistical methods and application in medical product development Assists readers in undertaking design and analysis of experiments at various stages of product development Features case studies throughout the book, as well as, SAS and R code

Explores computer-intensive probability and statistics for ecosystem management decision making Simulation is an accessible way to explain probability and stochastic model behavior to beginners. This book introduces probability and statistics to future and practicing ecosystem managers by providing a comprehensive treatment of these two areas. The author presents a self-contained introduction for individuals involved in monitoring, assessing, and managing ecosystems and features intuitive, simulation-based explanations of probabilistic and statistical concepts. Mathematical programming details are provided for estimating ecosystem model parameters with Minimum Distance, a robust and computer-intensive method. The majority of examples illustrate how probability and statistics can be applied to ecosystem management challenges. There are over 50 exercises – making this book suitable for a lecture course in a natural resource and/or wildlife management department, or as the main text in a program of self-study. Key features: Reviews different approaches to wildlife and ecosystem management and inference. Uses simulation as an accessible way to explain probability and stochastic model behavior to beginners. Covers material from basic probability through to hierarchical Bayesian models and spatial/ spatio-temporal statistical inference. Provides detailed instructions for using R, along with complete R programs to recreate the output of the many examples presented. Provides an introduction to Geographic Information Systems (GIS) along with examples from Quantum GIS, a free GIS software package. A companion website featuring all R code and data used throughout the book. Solutions to all exercises are presented along with an online intelligent tutoring system that supports readers who are using the book for self-study.

Fully revised and updated, this book combines a theoretical background with examples and references to R, MINITAB and JMP, enabling practitioners to find state-of-the-art material on both foundation and implementation tools to support their work. Topics addressed include computer-intensive data analysis, acceptance sampling, univariate and multivariate statistical process control, design of experiments, quality by design, and reliability using classical and Bayesian methods. The book can be used for workshops or courses on acceptance sampling, statistical process control, design of experiments, and reliability. Graduate and post-graduate students in the areas of statistical quality and engineering, as well as industrial statisticians, researchers and practitioners in these fields will all benefit from the comprehensive combination of theoretical and practical information provided in this single volume. Modern Industrial Statistics: With applications in R, MINITAB and JMP: Combines a practical approach with theoretical foundations and computational support. Provides examples in R using a dedicated package called MISTAT, and also refers to MINITAB and JMP. Includes exercises at the end of each chapter to aid learning and test knowledge. Provides over 40 data sets representing real-life case studies. Is complemented by a comprehensive website providing an introduction to R, and installations of JMP scripts and MINITAB macros, including effective tutorials with introductory material: www.wiley.com/go/modern_industrial_statistics.

An essential, up-to-date guide to the design of studies and selection of the correct QoL instruments for observational studies and clinical trials. Quality of Life (QoL) outcomes or Person/Patient Reported Outcome Measures (PROMs) are now frequently being used in randomised controlled trials (RCTs) and observational studies. This book provides a practical guide to the design, analysis and interpretation of studies that use such outcomes. QoL outcomes tend to generate data with discrete, bounded and skewed distributions. Many investigators are concerned about the appropriateness of using standard statistical methods to analyse QoL data and want guidance on what methods to use. QoL outcomes are frequently used in cross-sectional surveys and non-randomised health-care evaluations. Provides a user-friendly guide to the design and analysis of clinical trials and observational studies in relation to QoL outcomes. Discusses the problems caused by QoL outcomes and presents intervention options to help tackle them. Guides the reader step-by-step through the selection of appropriate QoLs. Features exercises and solutions and a supporting website providing downloadable data files. Illustrated throughout with examples and case studies drawn from the author’s experience, this book offers statisticians and clinicians guidance on choosing between the numerous available QoL instruments.

The development and application of multivariate statisticaltechniques in process monitoring has gained substantial interestover the past two decades in academia and industry alike. Initially developed for monitoring and fault diagnosis in complexsystems, such techniques have been refined and applied in variousengineering areas, for example mechanical and manufacturing,chemical, electrical and electronic, and power engineering. The recipe for the tremendous interest in multivariate statisticaltechniques lies in its simplicity and adaptability for developingmonitoring applications. In contrast, competitive model,signal or knowledge based techniques showed their potential onlywhenever cost-benefit economics have justified the required effortin developing applications. Statistical Monitoring of Complex Multivariate Processespresents recent advances in statistics based process monitoring,explaining how these processes can now be used in areas such asmechanical and manufacturing engineering for example, in additionto the traditional chemical industry. This book: Contains a detailed theoretical background of the componenttechnology. Brings together a large body of work to address thefield’s drawbacks, and develops methods for theirimprovement. Details cross-disciplinary utilization, exemplified by examplesin chemical, mechanical and manufacturing engineering. Presents real life industrial applications, outliningdeficiencies in the methodology and how to address them. Includes numerous examples, tutorial questions and homeworkassignments in the form of individual and team-based projects, toenhance the learning experience. Features a supplementary website including Matlab algorithmsand data sets. This book provides a timely reference text to the rapidlyevolving area of multivariate statistical analysis for academics,advanced level students, and practitioners alike.