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Model-Based Recursive Partitioning with Adjustment for Measurement Error

Applied to the Cox's Proportional Hazards and Weibull Model

Language EnglishEnglish
Book Paperback
Book Model-Based Recursive Partitioning with Adjustment for Measurement Error Hanna Birke
Libristo code: 09136900
Publishers Springer Fachmedien Wiesbaden, January 2015
Model-based recursive partitioning (MOB) provides a powerful synthesis between machine-learning insp... Full description
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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.

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About the book

Full name Model-Based Recursive Partitioning with Adjustment for Measurement Error
Author Hanna Birke
Language English
Binding Book - Paperback
Date of issue 2015
Number of pages 240
EAN 9783658085049
ISBN 3658085045
Libristo code 09136900
Weight 3451
Dimensions 148 x 210 x 213
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