Drawing on various real-world applications, Sample Sizes for Clinical Trials takes readers through the process of calculating sample sizes for many types of clinical trials. It provides descriptions of the calculations with a practical emphasis.Focusing on normal, binary, ordinal, and survival data, the book explores a range of trials, including su
Drawing on various real-world applications, Sample Sizes for Clinical Trials takes readers through the process of calculating sample sizes for many types of clinical trials. It provides descriptions of the calculations with a practical emphasis.Focusing on normal, binary, ordinal, and survival data, the book explores a range of trials, including su
All new medicines and devices undergo early phase trials to assess, interpret and better understand their efficacy, tolerability and safety. An Introduction to Statistics in Early Phase Trials describes the practical design and analysis of these important early phase clinical trials and provides the crucial statistical basis for their interpretation. It clearly and concisely provides an overview of the most common types of trials undertaken in early phase clinical research and explains the different methodologies used. The impact of statistical technologies on clinical development and the statistical and methodological basis for making clinical and investment decisions are also explained. Conveys key ideas in a concise manner understandable by non-statisticians Explains how to optimise designs in a constrained or fixed resource setting Discusses decision making criteria at the end of Phase II trials Highlights practical day-to-day issues and reporting of early phase trials An Introduction to Statistics in Early Phase Trials is an essential guide for all researchers working in early phase clinical trial development, from clinical pharmacologists and pharmacokineticists through to clinical investigators and medical statisticians. It is also a valuable reference for teachers and students of pharmaceutical medicine learning about the design and analysis of clinical trials.
Epilepsy is a difficult illness to control; up to 35% of patients do not respond fully to traditional medical treatments. For this reason, many sufferers choose to rely on or incorporate complementary and alternative medicine (CAM) into their treatment regimens. Written for physicians, knowledgeable laypersons, and other professionals, Complementary and Alternative Therapies for Epilepsy bridges the worlds of traditional medicine and CAM to foster a broader perspective of healthcare for patients. The book respects cultural differences that may incorporate alternative medicine into a medical management program, and encourages patients to safely continue receiving necessary medical treatments. Wherever possible, scientific evidence supports the choice of treatment modalities, as well as the effectiveness of a combined traditional and CAM approach. Readers will find incisive discussions in sections on: Learning to Reduce Seizures Asian, Herbal and Homeopathic Therapies Nutritional Therapies Alternative Medical Therapies Oxygen Therapies Manipulation and Osteopathic Therapies Music, Art, and Pet Therapies From stress and epilepsy, to acupuncture, massage, craniosacral therapies, homeopathy, ketogenic diets, aromatherapy, hypnosis, and more, the book is all-inclusive and enlightening. Additional commentary by the editors provides a critical vantage point from which to interpret the data and viewpoints of the contributors, all experts in the therapies presented. This balanced, scientific approach will appeal to even those most skeptical of alternative therapies, making the book essential for every professional who seeks to provide the broadest range of effective patient care.
Power Analysis of Trials with Multilevel Data is a valuable reference for anyone who wants to perform power calculations on trials with hierarchical data. It provides a thorough overview of power analysis, familiarizing you with terminology and notation, outlining the key concepts of statistical power and power analysis, and covering all common hierarchical designs.
For more than 30 years, Designing Clinical Research has set the standard as the most practical, authoritative guide for physicians, nurses, pharmacists, and other practitioners involved in all forms of clinical and public health research. Using a reader-friendly writing style, Drs. Warren S. Browner, Thomas B. Newman, Steven R. Cummings, Deborah G. Grady, Alison J. Huang, Alka M. Kanaya, and Mark J. Pletcher, all of the University of California, San Francisco, provide up-to-date, commonsense approaches to the challenging judgments involved in designing, funding, and implementing a study. This state-of-the-art fifth edition features new figures, tables, and design, as well as new editors, new content, and extensively updated references to keep you current.
Designing Clinical Research sets the standard for providing a practical guide to planning, tabulating, formulating, and implementing clinical research, with an easy-to-read, uncomplicated presentation. This product incorporates current research methodology--including molecular and genetic clinical research--and offers an updated syllabus for conducting a clinical research workshop. Emphasis is on common sense as the main ingredient of good science. The book explains how to choose well-focused research questions and details the steps through all the elements of study design, data collection, quality assurance, and basic grant-writing.
All new medicines and devices undergo early phase trials to assess, interpret and better understand their efficacy, tolerability and safety. An Introduction to Statistics in Early Phase Trials describes the practical design and analysis of these important early phase clinical trials and provides the crucial statistical basis for their interpretation. It clearly and concisely provides an overview of the most common types of trials undertaken in early phase clinical research and explains the different methodologies used. The impact of statistical technologies on clinical development and the statistical and methodological basis for making clinical and investment decisions are also explained. Conveys key ideas in a concise manner understandable by non-statisticians Explains how to optimise designs in a constrained or fixed resource setting Discusses decision making criteria at the end of Phase II trials Highlights practical day-to-day issues and reporting of early phase trials An Introduction to Statistics in Early Phase Trials is an essential guide for all researchers working in early phase clinical trial development, from clinical pharmacologists and pharmacokineticists through to clinical investigators and medical statisticians. It is also a valuable reference for teachers and students of pharmaceutical medicine learning about the design and analysis of clinical trials.
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