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Añadir al carritoTaschenbuch. Condición: Neu. Competing Risks and Multistate Models with R | Jan Beyersmann (u. a.) | Taschenbuch | xi | Englisch | 2011 | Humana | EAN 9781461420347 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
Publicado por Springer New York, Springer US Nov 2011, 2011
ISBN 10: 1461420342 ISBN 13: 9781461420347
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models). Both R and multistate methods are promoted with a focus on nonparametric methods.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch.
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Competing Risks and Multistate Models with R covers models that generalize the analysis of time to a single event. Both R and multistate methods are promoted with a focus on nonparametric methods.This book explains hazard-based analyses of competing risks and multistate data with R. Special emphasis is placed on the interpretation of the results. A unique feature of this book is that readers are encouraged to simulate their own data based on the transition hazards only, which are the key quantities of the subsequent analyses. This simulation-based approach is supplemented with real data examples from studies in clinical medicine where the authors have been involved.This book is aimed at data analysts, with a background in standard survival analysis, who wish to understand, analyse and interpret more complex event histories with R. It is also suitable for graduate courses in biostatistics, statistics and epidemiological methods with a focus on non- and semiparametric methods. The real data examples, R packages, and the entire R code used in the book are available online.
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Idioma: Inglés
Publicado por Springer-Verlag New York Inc., 2011
ISBN 10: 1461420342 ISBN 13: 9781461420347
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
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Añadir al carritoPaperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Idioma: Inglés
Publicado por Springer New York, Springer US Nov 2011, 2011
ISBN 10: 1461420342 ISBN 13: 9781461420347
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 96,29
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Competing Risks and Multistate Models with R covers models that generalize the analysis of time to a single event. Both R and multistate methods are promoted with a focus on nonparametric methods.This book explains hazard-based analyses of competing risks and multistate data with R. Special emphasis is placed on the interpretation of the results. A unique feature of this book is that readers are encouraged to simulate their own data based on the transition hazards only, which are the key quantities of the subsequent analyses. This simulation-based approach is supplemented with real data examples from studies in clinical medicine where the authors have been involved.This book is aimed at data analysts, with a background in standard survival analysis, who wish to understand, analyse and interpret more complex event histories with R. It is also suitable for graduate courses in biostatistics, statistics and epidemiological methods with a focus on non- and semiparametric methods. The real data examples, R packages, and the entire R code used in the book are available online. 260 pp. Englisch.
Librería: moluna, Greven, Alemania
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Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book enables the reader to analyse complex time-to-event data himself, using the free open source language R for statistical computing The data situations considered are competing risks--several, mutually exclusive event types and multist.