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This book provides not only the theory of biostatistics, but also the opportunity of applying it in practice. In fact, each chapter presents one or more specific examples on how to perform an epidemiological or statistical data analysis and includes download access to the software and databases, giving the reader the possibility of replicating the analyses described.
Applies traditional epideiologic methods for determining disease etiology to the real-life applications of public health and health services research. This text contains a chapter on the development and use of systematic reviews and one on epidemiology and the law.
Bias analysis quantifies the influence of systematic error on an epidemiology study’s estimate of association. The fundamental methods of bias analysis in epi- miology have been well described for decades, yet are seldom applied in published presentations of epidemiologic research. More recent advances in bias analysis, such as probabilistic bias analysis, appear even more rarely. We suspect that there are both supply-side and demand-side explanations for the scarcity of bias analysis. On the demand side, journal reviewers and editors seldom request that authors address systematic error aside from listing them as limitations of their particular study. This listing is often accompanied by explanations for why the limitations should not pose much concern. On the supply side, methods for bias analysis receive little attention in most epidemiology curriculums, are often scattered throughout textbooks or absent from them altogether, and cannot be implemented easily using standard statistical computing software. Our objective in this text is to reduce these supply-side barriers, with the hope that demand for quantitative bias analysis will follow.
This book is an expanded version of the Kahn's widely used text, An Introduction to Epidemiologic Methods (Oxford, 1983). It provides clear insight into the basic statistical tools used in epidemiology and is written so that those without advanced statistical training can comprehend the ideas underlying the analytical techniques. The authors emphasize the extent to which similar results are obtained from different methods, both simple and complex. To this edition they have added a new chapter on "Comparison of Numerical Results for Various Methods of Adjustment" and also one on "The Primacy of Data Collection." New topics include the Kaplan-Meier product-limit method and the Cox proportional hazards model for analysis of time-related outcomes. An appendix of data from the Framingham Heart Study is used to illustrate the application of various analytical methods to an identical set of real data and provides source material for student exercises. The text has been updated throughout.
This book will familiarize your students with basic principles of epidemiology and biostatistics. Designed for use in a single course, it will clarify the distinction and complementary roles of epidemiology and biostatistics in a range of settings, and train students on the complementary roles epidemiology and biostatistics play in carrying out selected activities in the health professions.
Get a quick, expert overview of the many key facets of heart failure research with this concise, practical resource by Dr. Longjian Liu. This easy-to-read reference focuses on the incidence, distribution, and possible control of this significant clinical and public health problem which is often associated with higher mortality and morbidity, as well as increased healthcare expenditures. This practical resource brings you up to date with what's new in the field and how it can benefit your patients. - Features a wealth of information on epidemiology and research methods related to heart failure. - Discusses pathophysiology and risk profile of heart failure, research and design, biostatistical basis of inference in heart failure study, advanced biostatistics and epidemiology applied in heart failure study, and precision medicine and areas of future research. - Consolidates today's available information and guidance in this timely area into one convenient resource.
Emphasizing interpretation of results, this hands-on guide explains why, when, and how to use mixed models with your data.
Over the past decades, epidemiology has made a relevant contribution to public health by identifying health problems and analysing their determinants. Recent developments call for new and applied methods to support the planning, implementation and evaluation of public health policies and programmes. This book presents an integrated overview of such epidemiological methods, to be used within the joined working process of several public health disciplines. It provides relevant theories, concepts and tools, illustrated with practical examples in order to empower epidemiologists in public health.The first part of this book describes epidemiological history in a nutshell and explains the relationship with the public health domain. It closes with the presentation of a joint work cycle for policy, practice and research: the public health cycle.Part two presents seven steps epidemiologists should follow to strengthen their contribution to the public health cycle: conduct a needs assessment, support priority setting, formulate aims and objectives, construct a logic model, develop an evaluation plan, perform quality control, and analyse processes and outcomes.Part three illustrates the institutional architecture of public health and describes the professional fields of policy and health promotion as knowledge of these major fields facilitates interdisciplinary collaboration in each stage of the public health cycle.This book is intended for students and epidemiologists in public health practice. It was written by 20 Dutch authors with either longstanding experience or fresh enthusiasm. The editors are all affiliated with Academic Collaborative Centres for Public Health in the Netherlands, which aim to bridge the gap between policy, practice and research.
INTRODUCTORY APPLIED BIOSTATISTICS (WITH CD-ROM) explores statistical applications in the medical and public health fields. Examples drawn directly from the authors' clinical experiences with applied biostatistics make this text both practical and applicable. You'll master application techniques by hand before moving on to computer applications, with SAS programming code and output for each technique covered in every chapter. For each topic, the book addresses methodology, including assumptions, statistical formulas, and appropriate interpretation of results. This book is a must-have for every student preparing for a statistical career in a healthcare field!
A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.