Clinical Data Analysis on a Pocket Calculator: Understanding the Scientific Methods of Statistical Reasoning and Hypothesis Testing, Cleophas Ton J., Zwinderman Aeilko H.
Автор: Ton J. Cleophas; Aeilko H. Zwinderman Название: Clinical Data Analysis on a Pocket Calculator ISBN: 3319271032 ISBN-13(EAN): 9783319271033 Издательство: Springer Рейтинг: Цена: 11753.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers all relevant pocket calculator statistical methods, making it an ideal resource for those who wish to understand statistics but have no time for complex mathematics. It helps facilitate data analysis by detailing pocket calculator methods.
Описание: Upgraded to reflect the latest research and software applications on the topic, this new edition continues to provide a comprehensive introduction to the statistical methods for analyzing survival data.
Автор: Van Houwelingen Название: Dynamic Prediction in Clinical Survival Analysis ISBN: 1439835330 ISBN-13(EAN): 9781439835333 Издательство: Taylor&Francis Рейтинг: Цена: 24499.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
There is a huge amount of literature on statistical models for the prediction of survival after diagnosis of a wide range of diseases like cancer, cardiovascular disease, and chronic kidney disease. Current practice is to use prediction models based on the Cox proportional hazards model and to present those as static models for remaining lifetime after diagnosis or treatment. In contrast, Dynamic Prediction in Clinical Survival Analysis focuses on dynamic models for the remaining lifetime at later points in time, for instance using landmark models.
Designed to be useful to applied statisticians and clinical epidemiologists, each chapter in the book has a practical focus on the issues of working with real life data. Chapters conclude with additional material either on the interpretation of the models, alternative models, or theoretical background. The book consists of four parts:
Part I deals with prognostic models for survival data using (clinical) information available at baseline, based on the Cox model
Part II is about prognostic models for survival data using (clinical) information available at baseline, when the proportional hazards assumption of the Cox model is violated
Part III is dedicated to the use of time-dependent information in dynamic prediction
Part IV explores dynamic prediction models for survival data using genomic data
Dynamic Prediction in Clinical Survival Analysis summarizes cutting-edge research on the dynamic use of predictive models with traditional and new approaches. Aimed at applied statisticians who actively analyze clinical data in collaboration with clinicians, the analyses of the different data sets throughout the book demonstrate how predictive models can be obtained from proper data sets.
Описание: of the spectral density I obtained by applying a certain statistical procedure to the observed values of the variables Xl` . , X , usually depends in n a complicated manner on the cyclic frequency). , are approximated by values of a certain sufficiently simple function 1 = 1
Описание: With a near 50% divorce rate in the United States, every parent who reads this book is either going through a divorce, has been divorced, is married to or living with someone who is divorced, or will go through one or more of his/her children`s divorces. Unlike books designed to enlighten parents about children`s reactions to divorce, A Parents` Guide to Child Custody is written for parents themselves. The book provides parents with an overview of the context within which custody is decided by courts today, including a chapter-by-chapter explanation of the factors that are considered by the court in rendering a custody decision. Part I opens the book with three brief case histories in which the reader is asked to put herself/himself in the place of the court by imaging what custody decisions they would make if they were the judge. This chapter is followed by an orientation to the three major factors that all courts consider in coming to a custody decision. Each subsequent chapter addresses the specific factors that are weighed by the court in its deliberations. Part II provides a more in-depth view of such topics as the factors considered by judges in coming to a custody decision, what to expect when undergoing a child custody evaluation, the use and pitfalls of psychological tests, the assessment of parental capacity, and strategies for countering false allegations. Part III reviews eight myths (i.e. commonly held misconceptions) about what is best for children, as well as guidelines for discussing custody with your children. Part IV provides insight into how best to deal with parental alienation, domestic violence, and obstruction of one parent`s access by the other parent after the court has ruled on custody. Part V concludes with eight sure-fire ways to lose custody as well as the custody evaluator`s recommendations in each of the three hypothetical cases presented in Part I. It is the author`s sincere hope that this book will help parents become better advocates for themselves and for their children.
Автор: Kedem Benjamin Et Al Название: Statistical Data Fusion ISBN: 9813200189 ISBN-13(EAN): 9789813200180 Издательство: World Scientific Publishing Рейтинг: Цена: 12830.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 'The book provides a comprehensive review of the DRM approach to data fusion. It is well written and easy to follow, although the technical details are not trivial. The authors did an excellent job in making a concise introduction of the statistical techniques in data fusion. The book contains several real data ... Overall, I found that the book covers an important topic and the DRM is a promising tool in this area. Researchers on data fusion will surely find this book very helpful and I will use this book in studying with my PhD students.'Journal of the American Statistical AssociationThis book comes up with estimates or decisions based on multiple data sources as opposed to more narrowly defined estimates or decisions based on single data sources. And as the world is awash with data obtained from numerous and varied processes, there is a need for appropriate statistical methods which in general produce improved inference by multiple data sources.The book contains numerous examples useful to practitioners from genomics. Topics range from sensors (radars), to small area estimation of body mass, to the estimation of small tail probabilities, to predictive distributions in time series analysis.
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