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Verlag: Springer, 2019
ISBN 10: 3030163989ISBN 13: 9783030163983
Anbieter: SpringBooks, Berlin, Deutschland
Buch
Hardcover. Zustand: Very Good. 2. Auflage. Unread, some shelfwear. Immediately dispatched from Germany.
Verlag: Springer International Publishing 2019-08-01, Berlin, 2019
ISBN 10: 3030163989ISBN 13: 9783030163983
Anbieter: Blackwell's, London, Vereinigtes Königreich
Buch
hardback. Zustand: New. Language: ENG.
Verlag: Springer International Publishing, 2020
ISBN 10: 3030164012ISBN 13: 9783030164010
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but a sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice.There is an increasing need for personalized evidence-based medicine that uses an individualized approach to medical decision-making. In this Big Data era, there is expanded access to large volumes of routinely collected data and an increased number of applications for prediction models, such as targeted early detection of disease and individualized approaches to diagnostic testing and treatment. Clinical Prediction Models presents a practical checklist that needs to be considered for development of avalid prediction model. Steps include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation formatting. The text also addresses common issues that make prediction models suboptimal, such as small sample sizes, exaggerated claims, and poor generalizability.The text is primarily intended for clinical epidemiologists and biostatisticians. Including many case studies and publicly available R code and data sets, the book is also appropriate as a textbook for a graduate course on predictive modeling in diagnosis and prognosis. While practical in nature, the book also provides a philosophical perspective on data analysis in medicine that goes beyond predictive modeling.Updates to this new and expanded edition include:-A discussion of Big Data and its implications for the design of prediction models-Machine learning issues-More simulations with missing 'y' values-Extended discussion on between-cohort heterogeneity-Description of ShinyApp-Updated LASSO illustration-New case studies.
Verlag: Springer, 2008
ISBN 10: 038777243XISBN 13: 9780387772431
Anbieter: WorldofBooks, Goring-By-Sea, WS, Vereinigtes Königreich
Buch
Hardback. Zustand: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Verlag: Springer, 2019
ISBN 10: 3030163989ISBN 13: 9783030163983
Anbieter: Monster Bookshop, Fleckney, Vereinigtes Königreich
Buch
hardcover. Zustand: New. BRAND NEW ** SUPER FAST SHIPPING FROM UK WAREHOUSE ** 30 DAY MONEY BACK GUARANTEE.
Verlag: Springer International Publishing, 2019
ISBN 10: 3030163989ISBN 13: 9783030163983
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The second edition of this volume provides insight and practical illustrations on how modern statistical concepts and regression methods can be applied in medical prediction problems, including diagnostic and prognostic outcomes. Many advances have been made in statistical approaches towards outcome prediction, but a sensible strategy is needed for model development, validation, and updating, such that prediction models can better support medical practice.There is an increasing need for personalized evidence-based medicine that uses an individualized approach to medical decision-making. In this Big Data era, there is expanded access to large volumes of routinely collected data and an increased number of applications for prediction models, such as targeted early detection of disease and individualized approaches to diagnostic testing and treatment. Clinical Prediction Models presents a practical checklist that needs to be considered for development of avalid prediction model. Steps include preliminary considerations such as dealing with missing values; coding of predictors; selection of main effects and interactions for a multivariable model; estimation of model parameters with shrinkage methods and incorporation of external data; evaluation of performance and usefulness; internal validation; and presentation formatting. The text also addresses common issues that make prediction models suboptimal, such as small sample sizes, exaggerated claims, and poor generalizability.The text is primarily intended for clinical epidemiologists and biostatisticians. Including many case studies and publicly available R code and data sets, the book is also appropriate as a textbook for a graduate course on predictive modeling in diagnosis and prognosis. While practical in nature, the book also provides a philosophical perspective on data analysis in medicine that goes beyond predictive modeling.Updates to this new and expanded edition include:-A discussion of Big Data and its implications for the design of prediction models-Machine learning issues-More simulations with missing 'y' values-Extended discussion on between-cohort heterogeneity-Description of ShinyApp-Updated LASSO illustration-New case studies.
Verlag: Springer, 2008
ISBN 10: 038777243XISBN 13: 9780387772431
Anbieter: medimops, Berlin, Deutschland
Buch
Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
Verlag: Springer International Publishing, 2019
ISBN 10: 3030163989ISBN 13: 9783030163983
Anbieter: moluna, Greven, Deutschland
Buch
Gebunden. Zustand: New. Ewout Steyerberg worked for 25 years at Erasmus Medical Center in Rotterdam before moving to Leiden where he is now Professor of Clinical Biostatistics and Medical Decision Making and chair of the Department of Biomedical Data Sciences at Leiden Univ.
Verlag: Springer New York, 2008
ISBN 10: 038777243XISBN 13: 9780387772431
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Prediction models are important in various fields, including medicine, physics, meteorology, and finance. Prediction models will become more relevant in the medical field with the increase in knowledge on potential predictors of outcome, e.g. from genetics. Also, the number of applications will increase, e.g. with targeted early detection of disease, and individualized approaches to diagnostic testing and treatment. The current era of evidence-based medicine asks for an individualized approach to medical decision-making. Evidence-based medicine has a central place for meta-analysis to summarize results from randomized controlled trials; similarly prediction models may summarize the effects of predictors to provide individu- ized predictions of a diagnostic or prognostic outcome. Why Read This Book My motivation for working on this book stems primarily from the fact that the development and applications of prediction models are often suboptimal in medical publications. With this book Ihope to contribute to better understanding of relevant issues and give practical advice on better modelling strategies than are nowadays widely used. Issues include: (a) Better predictive modelling is sometimes easily possible; e.g. a large data set with high quality data is available, but all continuous predictors are dich- omized, which is known to have several disadvantages.
Verlag: Springer 01 D, 2010
ISBN 10: 1441926488ISBN 13: 9781441926487
Anbieter: AwesomeBooks, Wallingford, Vereinigtes Königreich
Buch
Paperback. Zustand: Very Good. Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating (Statistics for Biology and Health) This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .