Comprehensive guide to basic principles of epidemiology and biostatistics. Concise study notes and exercises are included. Emphasis is on application. This edition includes a revised chapter on the appraisal of epidemiological studies, a new section on meta-analysis, and more.

The Fifth Edition of this popular text is your student's comprehensive study guide to the basic principles of both epidemiology and biostatistics. Clear and concise study notes and exercises help your students learn and apply concepts in epidemiology and biostatistics, while multiple-choice examinations test their understanding. Application of these concepts to critical assessment of epidemiologic studies is emphasized. This updated and revised New Edition includes: A new section on meta-analysis; revised self-assessment exercises; coverage of primary, secondary, and tertiary prevention in the context of screening for disease.

Help your students understand some of the most elusive fundamentals of epidemiology and biostatistics with this fully updated revision of the bestselling Study Guide to Epidemiology and Biostatistics. The Seventh Edition offers expanded chapters as well as coverage of new topics that have become prevalent in the medical literature such as: receiver-operator curve analysis to improve sensitivity/specificity; the power of a statistical test; one-tailed P values; comparison-wise significance levels versus study-wise significance levels; confidence interval and its relationship to statistical significance; meta-analysis with current methods for assessing heterogeneity and the potential for publication bias; and the use of propensity scoring to reduce bias in non-experimental studies. Key Features: • 46 objectives, expressed in behavioral terms, cite the concepts to be learned and the level at which students are expected to perform • Study Notes, which can be used as the sole source of input to cover the material or used to supplement attendance at a lecture series • Chapter Exercises, which encourage students to immediately use their newly acquired knowledge, and thus improve retention through practice • Multiple Choice Examinations, which have the same scope and are on the same level that students may expect to encounter in professional examinations

Since it first appeared in 1996, the open-source programming language R has become increasingly popular as an environment for statistical analysis and graphical output. In addition to being freely available, R offers several advantages for biostatistics, including strong graphics capabilities, the ability to write customized functions, and its extensibility. This is the first textbook to present classical biostatistical analysis for epidemiology and related public health sciences to students using the R language. Based on the assumption that readers have minimal familiarity with statistical concepts, the author uses a step-bystep approach to building skills. The text encompasses biostatistics from basic descriptive and quantitative statistics to survival analysis and missing data analysis in epidemiology. Illustrative examples, including real-life research problems and exercises drawn from such areas as nutrition, environmental health, and behavioral health, engage students and reinforce the understanding of R. These examples illustrate the replication of R for biostatistical calculations and graphical display of results. The text covers both essential and advanced techniques and applications in biostatistics that are relevant to epidemiology. This text is supplemented with teaching resources, including an online guide for students in solving exercises and an instructor's manual. KEY FEATURES: First overview biostatistics textbook for epidemiology and public health that uses the open-source R program Covers essential and advanced techniques and applications in biostatistics as relevant to epidemiology Features abundant examples and exercises to illustrate the application of R language for biostatistical calculations and graphical displays of results Includes online student solutions guide and instructor's manual

Help your students understand some of the most elusive fundamentals of epidemiology and biostatistics with this fully updated revision of the bestselling Study Guide to Epidemiology and Biostatistics. The Seventh Edition offers expanded chapters as well as coverage of new topics that have become prevalent in the medical literature such as: receiver-operator curve analysis to improve sensitivity/specificity; the power of a statistical test; one-tailed P values; comparison-wise significance levels versus study-wise significance levels; confidence interval and its relationship to statistical significance; meta-analysis with current methods for assessing heterogeneity and the potential for publication bias; and the use of propensity scoring to reduce bias in non-experimental studies. Important Notice: The digital edition of this book is missing some of the images or content found in the physical edition.

Epidemiology/Biostatistics

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Supplemented throughout by appropriate examples and helpful hints, this practical guide to the design, conduct, analysis and interpretation of epidemiological studies is designed to support and encourage new students as well as clinical professionals. --! From publisher's description.

From the Department of Epidemiology at Johns Hopkins University and continuing in the tradition of award-winning educator and epidemiologist Dr. Leon Gordis, comes the fully revised 6th Edition of Gordis Epidemiology. This bestselling text provides a solid introduction to basic epidemiologic principles as well as practical applications in public health and clinical practice, highlighted by real-world examples throughout. New coverage includes expanded information on genetic epidemiology, epidemiology and public policy, and ethical and professional issues in epidemiology, providing a strong basis for understanding the role and importance of epidemiology in today's data-driven society. - Covers the basic principles and concepts of epidemiology in a clear, uniquely memorable way, using a wealth of full-color figures, graphs, charts, and cartoons to help you understand and retain key information. - Reflects how epidemiology is practiced today, with a new chapter organization progressing from observation and developing hypotheses to data collection and analyses. - Features new end-of-chapter questions for quick self-assessment, and a glossary of genetic terminology. - Provides more than 200 additional multiple-choice epidemiology self-assessment questions online. - Evolve Instructor Resources, including a downloadable image and test bank, are available to instructors through their Elsevier sales rep or via request at: https://evolve.elsevier.com

Statistical ideas have been integral to the development of epidemiology and continue to provide the tools needed to interpret epidemiological studies. Although epidemiologists do not need a highly mathematical background in statistical theory to conduct and interpret such studies, they do need more than an encyclopedia of "recipes." Statistics for Epidemiology achieves just the right balance between the two approaches, building an intuitive understanding of the methods most important to practitioners and the skills to use them effectively. It develops the techniques for analyzing simple risk factors and disease data, with step-by-step extensions that include the use of binary regression. It covers the logistic regression model in detail and contrasts it with the Cox model for time-to-incidence data. The author uses a few simple case studies to guide readers from elementary analyses to more complex regression modeling. Following these examples through several chapters makes it easy to compare the interpretations that emerge from varying approaches. Written by one of the top biostatisticians in the field, Statistics for Epidemiology stands apart in its focus on interpretation and in the depth of understanding it provides. It lays the groundwork that all public health professionals, epidemiologists, and biostatisticians need to successfully design, conduct, and analyze epidemiological studies.