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Model-Based Recursive Partitioning with Adjustment for Measurement Error [[electronic resource] ] : Applied to the Cox’s Proportional Hazards and Weibull Model / / by Hanna Birke



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Autore: Birke Hanna Visualizza persona
Titolo: Model-Based Recursive Partitioning with Adjustment for Measurement Error [[electronic resource] ] : Applied to the Cox’s Proportional Hazards and Weibull Model / / by Hanna Birke Visualizza cluster
Pubblicazione: Wiesbaden : , : Springer Fachmedien Wiesbaden : , : Imprint : Springer Spektrum, , 2015
Edizione: 1st ed. 2015.
Descrizione fisica: 1 online resource (259 p.)
Disciplina: 510
518
570.285
614.5999
Soggetto topico: Computer mathematics
Biomathematics
Cancer research
Computational Mathematics and Numerical Analysis
Mathematical and Computational Biology
Cancer Research
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references.
Nota di contenuto: 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.
Sommario/riassunto: 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.  .
Titolo autorizzato: Model-Based Recursive Partitioning with Adjustment for Measurement Error  Visualizza cluster
ISBN: 3-658-08505-3
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910304131903321
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Serie: BestMasters, . 2625-3577