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Modern Thoracic Oncology is the first comprehensive publication on thoracic oncology. Contributors who are world experts have authored concise, relevant and current topics in this field. Whether one desires information regarding lung cancer screening, esophageal cancer staging, mutational analysis, targeted therapies, stereotactic ablative radiation with real-time imaging, minimally-invasive and robotic surgery, combination immunotherapy, microwave/cryoablation, or methods of early cancer detection, this set of three volumes, encompass all of the latest information in the field of thoracic oncology. A rapidly advancing knowledgebase has led to dramatic improvements in individualized or 'pers...
This new edition provides the essential clinical guidance both for those embarking upon a career in palliative medicine and for those already established in the field. A team of international experts here distil what every practitioner needs to know into a practical and reliable resource.
Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized stru...
Handbook of Supportive Oncology and Palliative Care is a practical guide to providing evidence-based and value-based care to adult and pediatric cancer patients experiencing severe symptoms and stressors due to cancer diagnosis, cancer treatment, and comorbid conditions. This accessible reference provides the art and science behind the whole-person and family approach to care by delivering the best practices to relieving a cancer patient’s symptoms across physical, psychosocial, and spiritual dimensions. Unlike other resources, this book covers all dimensions of palliative care but with a special emphasis on primary palliative care. Part One of the handbook provides the essential backgroun...
Structural equation modeling (SEM) is a very general and flexible multivariate technique that allows relationships among variables to be examined. The roots of SEM are in the social sciences. In writing this textbook, the authors look to make SEM accessible to a wider audience of researchers across many disciplines, addressing issues unique to health and medicine. SEM is often used in practice to model and test hypothesized causal relationships among observed and latent (unobserved) variables, including in analysis across time and groups. It can be viewed as the merging of a conceptual model, path diagram, confirmatory factor analysis, and path analysis. In this textbook the authors also dis...
This volume covers classic as well as cutting-edge topics on the analysis of clinical trial data in biomedical and psychosocial research and discusses each topic in an expository and user-friendly fashion. The intent of the book is to provide an overview of the primary statistical and data analytic issues associated with each of the selected topics, followed by a discussion of approaches for tackling such issues and available software packages for carrying out analyses. While classic topics such as survival data analysis, analysis of diagnostic test data and assessment of measurement reliability are well known and covered in depth by available topic-specific texts, this volume serves a diffe...
A timely and applied approach to the newly discovered methods and applications of U-statistics Built on years of collaborative research and academic experience, Modern Applied U-Statistics successfully presents a thorough introduction to the theory of U-statistics using in-depth examples and applications that address contemporary areas of study including biomedical and psychosocial research. Utilizing a "learn by example" approach, this book provides an accessible, yet in-depth, treatment of U-statistics, as well as addresses key concepts in asymptotic theory by integrating translational and cross-disciplinary research. The authors begin with an introduction of the essential and theoretical ...
This book compiles and presents new developments in statistical causal inference. The accompanying data and computer programs are publicly available so readers may replicate the model development and data analysis presented in each chapter. In this way, methodology is taught so that readers may implement it directly. The book brings together experts engaged in causal inference research to present and discuss recent issues in causal inference methodological development. This is also a timely look at causal inference applied to scenarios that range from clinical trials to mediation and public health research more broadly. In an academic setting, this book will serve as a reference and guide to a course in causal inference at the graduate level (Master's or Doctorate). It is particularly relevant for students pursuing degrees in statistics, biostatistics, and computational biology. Researchers and data analysts in public health and biomedical research will also find this book to be an important reference.