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This book addresses the challenge of presenting biostatistics to medical and health science audiences coherently. Tailored for students and researchers, its 13 chapters progress logically from foundational concepts like measurement scales and statistical calculations to advanced topics such as probability, correlation, regression and Health and disease measures. Practical examples enhance relevance, and its gradual approach ensures easy comprehension even for non-statisticians. The book's practical emphasis shines as it culminates in teaching the use of SPSS software for result interpretation, bridging theory and practice effectively. It empowers medical professionals to confidently understand and apply statistical concepts in their work, serving as an indispensable resource in navigating the intricacies of biostatistics in medical and health sciences.
Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background. The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. Using real data and including dozens of interesting data sets, this bestselling text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.
Evidence-based medicine aims to apply the best available evidence gained from the scientific method to medical decision making. It is a practice that uses statistical analysis of scientific methods and outcomes to drive further experimentation and diagnosis. The profusion of evidence-based medicine in medical practice and clinical research has produced a need for life scientists and clinical researchers to assimilate biostatistics into their work to meet efficacy and practical standards. Practical Biostatistics provides researchers, medical professionals, and students with a friendly, practical guide to biostatistics. With a detailed outline of implementation steps complemented by a review of important topics, this book can be used as a quick reference or a hands-on guide to effectively incorporate biostatistics in clinical trials. Customized presentation for biological investigators with examples taken from current clinical trials in multiple disciplines Clear and concise definitions and examples provide a pragmatic guide to bring clarity to the applications of statistics in improving human health Addresses the challenge of assimilation of mathematical concepts to better interpret literature, to build stronger studies, to present research effectively, and to improve communication with supporting biostatisticians
Practical Biostatistics: A Step-by-Step Approach for Evidence-Based Medicine, Second Edition presents a complete resource of biostatistical knowledge meant for health sciences students, researchers and health care professionals. The book's content covers the investigator’s hypothesis, collective health, observational studies, the biostatistics of intervention studies, clinical trials and additional concepts. Chapters are written in a didactic way, making them easier to comprehend by readers with little or no background on statistics. Evidence-based medicine aims to apply the best available evidence gained from the scientific method to medical decision-making using statistical analyses of scientific methods and outcomes to drive further experimentation and diagnosis. With a detailed outline of implementation steps complemented by a review of important topics, this book can be used as a quick reference or hands-on guide on how to effectively incorporate biostatistics in clinical trials and research projects. Explains biostatistics in a didactic way for students, researchers and professionals of health sciences with little or no background on mathematics Presents a new section dedicated to epidemiology and public health, broadening content from the previous edition Written by medical doctors with vast experience on biostatistics and teaching who develop the content based on real cases for better applicability by readers
There is an ever-increasing emphasis on evidence-based medicine that is distinguished by systematic crafting of the patient-centered research question, detailed literature searches, and careful appraisal of the resulting evidence. The consensus that ultimately emerges must then be applied in specific clinical settings, and it is to this process that translational effectiveness analysis refers. This portable and easy-to-use handbook is intended as a practical teaching guide on translational effectiveness for students and clinicians. Specifically, it will serve as a primer on patient-centered outcomes research methodology in the health sciences and explain how to acquire and understand the fundamental data that determine which reports are valued as the “best available” evidence. It presents an accessible and readily intelligible set of principles which doctors, dentists, nurses, and insurance carriers will be able to use in the process of health care-related decision-making. ​
*Customized presentation for biological investigators with examples taken from current clinical trials in multiple disciplines.
Anyone who attempts to read genetics or epidemiology research literature needs to understand the essentials of biostatistics. This book, a revised new edition of the successful Essentials of Biostatistics has been written to provide such an understanding to those who have little or no statistical background and who need to keep abreast of new findings in this fast moving field. Unlike many other elementary books on biostatistics, the main focus of this book is to explain basic concepts needed to understand statistical procedures. This Book: Surveys basic statistical methods used in the genetics and epidemiology literature, including maximum likelihood and least squares. Introduces methods, such as permutation testing and bootstrapping, that are becoming more widely used in both genetic and epidemiological research. Is illustrated throughout with simple examples to clarify the statistical methodology. Explains Bayes’ theorem pictorially. Features exercises, with answers to alternate questions, enabling use as a course text. Written at an elementary mathematical level so that readers with high school mathematics will find the content accessible. Graduate students studying genetic epidemiology, researchers and practitioners from genetics, epidemiology, biology, medical research and statistics will find this an invaluable introduction to statistics.
Encyclopedic in breadth, yet practical and concise, Medical Biostatistics, Fourth Edition focuses on the statistical aspects ofmedicine with a medical perspective, showing the utility of biostatistics as a tool to manage many medical uncertainties. This edition includes more topics in order to fill gaps in the previous edition. Various topics have been enlarged and modified as per the new understanding of the subject.
Most medical researchers, whether clinical or non-clinical, receive some background in statistics as undergraduates. However, it is most often brief, a long time ago, and largely forgotten by the time it is needed. Furthermore, many introductory texts fall short of adequately explaining the underlying concepts of statistics, and often are divorced from the reality of conducting and assessing medical research. Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background. The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. The text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.