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This practical guide shows why the analytic methods work and how to effectively analyze and interpret epidemiologic and medical survival data with the help of modern computer systems. The introduction presents a review of a variety of statistical methods that are not only key elements of survival analysis but are also central to statistical analysis in general. Techniques such as statistical tests, transformations, confidence intervals, and analytic modeling are presented in the context of survival data but are, in fact, statistical tools that apply to understanding the analysis of many kinds of data. Similarly, discussions of such statistical concepts such as bias, confounding, independence, and interaction are presented in the context of survival analysis as well as the basic components of a broad range of applications.

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Epidemiologic Research Methods in Public Health Practice is a unique book that focuses on quantitative methods in the field of epidemiology. This book stands out among other quantitative research texts, as it is one of the few to focus on the methods specific to the field of epidemiology, including procedures for protecting human subjects, sampling, recruiting, and research question formulation. It also contains methods for data collection, processing, and analysis, as well as techniques for publication, presentation, and funding. Epidemiologic Research Methods in Public Health Practice offers detailed treatment of the research steps along with tools to enhance students’ comprehension such as learning objectives, chapter outlines, templates, vocabulary, and study questions and exercises. Written from a real-world perspective This book is written from a real-world perspective, with a focus on threats to validity and reliability, as well as procedures to prevent and minimize them. It is a excellent guide for students of research methods in public health, and as a reference for both students and professionals as they conduct independent research. Key Features: • Details of every stage of a research project—from generating the research question to publishing results. • Study questions and exercises that can be used in the classroom or in independent research projects. • Lessons (including mistakes) learned from practical experience. • A comprehensive treatment of a particular stage of research in every chapter. • Specific examples of epidemiologic studies are used to illustrate procedures and concepts. Instructor Resources: Instructors's Manual, PowerPoint Lecture Slides, Test Bank

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Methods, just as diseases or scientists, have their own history. It is important for scientists to be aware of the genesis of the methods they use and of the context in which they were developed. A History of Epidemiologic Methods and Concepts is based on a collection of contributions which appeared in "SPM International Journal of Public Health", starting in January 2001. The contributions focus on the historical emergence of current epidemiological methods and their relative importance at different points in time, rather than on specific achievements of epidemiology in controlling plagues such as cholera, tuberculosis, malaria, typhoid fever, or lung cancer. The papers present the design of prospective and retrospective studies, and the concepts of bias, confounding, and interaction. The compilation of articles is complemented by an introduction and comments by Prof. Alfredo Morabia which puts them in the context of current epidemiological research.

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This is a rigorous, systematic introduction to the basic concepts and practical tools of epidemiologic research. It is aimed at readers who will be conducting epidemiologic studies themselves or who need a firm grasp of epidemiologic principles in order to interpret and evaluate studies conducted by others.
Besides offering clear descriptions of key concepts, the book is rich with examples illustrating how these concepts are applied. Some examples are drawn from classic studies in the field--the work of Snow, Semmelweis, Goldberger, Doll and Hill, and others--while many others concern modern-day epidemiologic studies of problems of current public health importance. Almost every chapter includes a set of exercises (with answers) to help students gain practice in applying new ideas and techniques.
The book's chapters are organized around three main themes: general concepts and methods of epidemiology; major study designs; and evaluating policies and programs. Collectively, these topics form the core material for a graduate-level course or course sequence in epidemiologic methods. Both authors are experienced epidemiologic researchers and have won multiple awards for effective teaching.

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Interpreting Epidemiologic Evidence: Strategies for Study Design and Analysis Description

Evaluating the strength or persuasiveness of epidemiologic evidence is inherently challenging, both for those new to the field and for experienced researchers. There are a myriad of potential biases to consider, but little guidance about how to asses the likely impact on study results. This book offers a strategy for assessing epidemiologic research findings, explicitly describing the goals and products of epidemiologic research in order to better evaluate it successes and limitations. The focus throughout is on practical tools for making optimal use of available data to assess whether hypothesized biases are operative and to anticipate concerns at the point of study design in order to ensure that needed information is generated. Specific tools for assessing the presence and impact of selection bias in both cohort and case-control studies, bias from non-response, confounding, exposure measurement error, disease measurement error, and random error are identified and evaluated. The potential value of each approach as well as its limitations are discussed, using examples from the published literature. Such information should help those who generate and interpret epidemiologic research to apply methodological principles more effectively to substantive issues, leading to a more accurate appraisal of the current evidence and greater clarity about research needs.