Handbook of Inter-Rater Reliability, 4th Edition


Book Description

The third edition of this book was very well received by researchers working in many different fields of research. The use of that text also gave these researchers the opportunity to raise questions, and express additional needs for materials on techniques poorly covered in the literature. For example, when designing an inter-rater reliability study, many researchers wanted to know how to determine the optimal number of raters and the optimal number of subjects that should participate in the experiment. Also, very little space in the literature has been devoted to the notion of intra-rater reliability, particularly for quantitative measurements. The fourth edition of this text addresses those needs, in addition to further refining the presentation of the material already covered in the third edition. Features of the Fourth Edition include: New material on sample size calculations for chance-corrected agreement coefficients, as well as for intraclass correlation coefficients. The researcher will be able to determine the optimal number raters, subjects, and trials per subject.The chapter entitled “Benchmarking Inter-Rater Reliability Coefficients” has been entirely rewritten.The introductory chapter has been substantially expanded to explore possible definitions of the notion of inter-rater reliability.All chapters have been revised to a large extent to improve their readability.







The Right Guide


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Silk


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Drug Utilization Research


Book Description

Towards a better understanding of how medicines are used in society Drug Utilization Research (DUR) is a discipline which combines aspects of pharmacotherapy, epidemiology, and health services research into an interdisciplinary set of methods for analyzing and assessing the prescribing, dispensing and consumption of medicines. It combines both qualitative and quantitative approaches to facilitate the safe and effective use of pharmaceuticals. Drug Utilization Research: Methods and Applications provides a comprehensive introduction to this discipline, prepared by an international team of authors with broad experience in numerous fields. Now reorganized and updated to reflect the latest research and global challenges, it is an indispensable resource for understanding the use of pharmaceuticals. Readers of the second edition of Drug Utilization Research will find: New chapters on methods, including more hands-on guidance on how to plan and conduct different types of drug utilization A section on specific applications in areas such as psychotropics, opioids, cancer drugs, antibacterials, and cardiovascular drugs A new section with case studies illustrating applications of DUR in different continents Detailed treatment of subjects including DUR and health policy, DUR in specific populations, and many more Drug Utilization Research is ideal for epidemiologists, pharmacists, physicians, nurses and others interested in drug use and its outcomes.




A Guide to Assessments That Work


Book Description

"This volume addresses the assessment of the most commonly encountered disorders or conditions among adults, older adults, and couples. Evidence-based strategies and instruments for assessing mood disorders, anxiety disorders, couple distress and sexual problems, health-related problems, and many other conditions are covered in depth. With a focus throughout on assessment instruments that are feasable, psychometrically sound, and useful for typical clinical practice, a rating system has been designed to provide evaluations of a measure's norms, reliability, validity, and clinical utility. Standardized tables summarize this information in each chapter, providing essential information on the most scientifically sound tools available for a range of assessment needs."--BOOK JACKET.




Interpretable Machine Learning


Book Description

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.