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OverviewModel-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. Full Product DetailsAuthor: Hanna BirkePublisher: Springer Fachmedien Wiesbaden Imprint: Springer Spektrum Edition: 2015 ed. Dimensions: Width: 14.80cm , Height: 1.50cm , Length: 21.00cm Weight: 3.451kg ISBN: 9783658085049ISBN 10: 3658085045 Pages: 240 Publication Date: 11 February 2015 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsReviewsAuthor InformationHanna 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. Tab Content 6Author Website:Countries AvailableAll regions |