Here is a book for clinicians, clinical investigators, trainees, and graduates who wish to develop their proficiency in the planning, execution, and interpretation of clinical and epidemiological research. Emphasis is placed on the design and analysis of research studies involving human subjects where the primary interest concerns principles of analytic (cause-and- effect) inference. The topic is presented from the standpoint of the clinician and assumes no previous knowledge of epidemiology, research design or statistics. Extensive use is made of illustrative examples from a variety of clinical specialties and subspecialties. The book is divided into three parts. Part I deals with epidemiological research design and analytic inference, including such issues as measurement, rates, analytic bias, and the main forms of observational and experimental epidemiological studies. Part II presents the principles and applications of biostatistics, with emphasis on statistical inference. Part III comprises four chapters covering such topics as diagnostic tests, decision analysis, survival (life-table) analysis, and causality.

Concise, fast-paced, intensive introduction to clinical research design for students and clinical research professionals Readers will gain sufficient knowledge to pass the United States Medical Licensing Examination part I section in Epidemiology

Examining the principles and methods of research on the evaluation of factors affecting the outcome of illness, this volume emphasizes diagnostic and therapeutic interventions--the factors most readily modified by health care providers. The author discusses various ways of structuring observations on patient groups, and appraises the nature and strength of inferences drawn from those observations. Weiss also demonstrates how the results of this type of research--clinical epidemiologic research--can be incorporated into the decision-making process utilized in clinical medicine. The Second edition differs from the earlier one in a number of respects. It now employs a broader frame of reference, which includes studies such as those of adverse drug effects that use multipurpose computerized databases, and an expanded, explanation of the structure of evidence for drawing inferences, particularly evidence pertaining to the efficacy of testing. Examples have been modernized and replaced with more recent experimental results throughout the text, while decision analysis has been de-emphasized. The book's underlying theme, however, remains the same: the resources available to health care are finite and, through properly conducted research, the most efficient and safest ways of using these resources can and should be identified.

“Methods of Clinical Epidemiology” serves as a text on methods useful to clinical researchers. It provides a clear introduction to the common research methodology specific to clinical research for both students and researchers. This book sets out to fill the gap left by texts that concentrate on public health epidemiology and focuses on what is not covered well in such texts. The four sections cover methods that have not previously been brought together in one text and serves as a second level textbook of clinical epidemiology methodology. This book will be of use to postgraduate students in clinical epidemiology as well as clinical researchers at the start of their careers.

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Biostatistics and Epidemiology/A Primer for Health Professionals offers practical guidelines and gives a concise framework for research and interpretation in the field. In addition to major sections covering statistics and epidemiology, the book includes a comprehensive exploration of scientific methodology, probability, and the clinical trial. The principles and methods described in this book are basic and apply to all medical subspecialties, psychology and education. The primer will be especially useful to public health officials and students looking for an understandable treatment of the subject.

This workbook is designed to teach the major fundamental concepts in Epidemiology, Biostatistics, and clinical research design alongside the textbook "Epidemiology and Biostatistics, 2nd Edition". It is written in concise and organized fashion with many examples to illustrate the concepts deriving from a collection of written materials created to teach Epidemiology and Biostatistics to medical students. The major differences from related titles include a “story” based approach toward teaching the material, relative brevity while maintaining focus on key concepts, and taking the perspective of first-time learners (avoiding and/or clearly defining jargon, using clear common-sense language). It features a variety of questions: long, short, and multiple choice questions. The workbook is made to provide students with the tools necessary to form their own informed conclusions from the clinical research literature.

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

The most important points in clinical biostatistics, presented intuitively with clinical examples. Valuable not only for biostatistics courses and medical board review, but for providing a lasting clear approach to interpreting medical research reports.