Model-Based Recursive Partitioning with Adjustment for Measurement Error Applied to the Cox’s Proportional Hazards and Weibull Model /

• Κύριος συγγραφέας: Birke, Hanna (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Spektrum, 2015.
• Σειρά: BestMasters
• Θέματα: Mathematics.; Cancer research.; Computer mathematics.; Biomathematics.; Computational Mathematics and Numerical Analysis.; Mathematical and Computational Biology.; Cancer Research.

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 econo...

Πίνακας περιεχομένων:

• 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.