Model-Based Recursive Partitioning with Adjustment for Measurement Error: Applied to the Cox’s Proportional Hazards and Weibull Model (BestMasters) - Softcover

Birke, Hanna

Softcover

ISBN 10: 3658085045 ISBN 13: 9783658085049

Publisher: Springer Spektrum, 2015

Synopsis

Die ersten beiden Sätze des Kurztextes für den Umschlag sollen die wichtigsten Vorteile und Kernaussagen Ihres Buches herausstellen. Einleitungssätze wie „In den letzten Jahren…“ o.Ä. sollen vermieden werden. Dies dient dazu, dem Buch die bestmögliche Aufmerksamkeit und Auffindbarkeit zu gewährleisten. Bei Google und Amazon werden beispielsweise häufig nur Vorschauen angezeigt. Daher ist es wichtig, die Verkaufsargumente direkt in den ersten beiden Sätzen, die in einer solchen Vorschau erscheinen würden, zu platzieren. Auch lesen viele potenzielle Käufer nicht den ganzen Umschlagtext, sondern nur die ersten 1 bis 2 Sätze. Am Ende des Kurztextes kann gern noch ein Model-based recursive partitioning (MOB) provides a powerful synthesis between machine-learning inspired recursive partitioning methods and regression models. Hanna Birke extends this approach by allowing in addition for measurement error in covariates, as frequently occurring in biometric (or econometric) studies, for instance, when measuring blood pressure or caloric intake per day. After an introduction into the background, the extended methodology is developed in detail for the Cox model and the Weibull model, carefully implemented in R, and investigated in a comprehensive simulation study.

About this title

About the Author

Hanna Birke wrote her master thesis under the supervision of Prof. Dr. Thomas Augustin at the department of statistics of the LMU Munich and is currently working on her doctoral thesis.

From the Back Cover

Model-based recursive partitioning (MOB) provides a powerful synthesis between machine-learning inspired recursive partitioning methods and regression models. Hanna Birke extends this approach by allowing in addition for measurement error in covariates, as frequently occurring in biometric (or econometric) studies, for instance, when measuring blood pressure or caloric intake per day. After an introduction into the background, the extended methodology is developed in detail for the Cox model and the Weibull model, carefully implemented in R, and investigated in a comprehensive simulation study.

Contents

• MOB and Measurement Error Modelling
• Derivation of an Adjusted MOB Algorithm for Covariates Measured with Error for the Cox and Weibull Model
• Implementation of the Suggested Method for the Weibull Model in the Open-Source Programming Language R
• Simulation Study Showing the Performance of the Implemented Method

Target Groups

• Researchers and students in the fields of statistics and cognate disciplines with interest in advanced modelling in combination with measurement error in covariates
• Data analysts of complex biometric or econometric studies with variables that are difficult to measure in practice

The Author

Hanna Birke wrote her master thesis under the supervision of Prof. Dr. Thomas Augustin at the department of statistics of the LMU Munich and is currently working on her doctoral thesis.

Edition details

• Publisher: Springer Spektrum
• Publication date: 2015
• Language: English
• ISBN 10: 3658085045
• ISBN 13: 9783658085049
• Binding: Paperback
• Number of pages: 264