Model-Based Recursive Partitioning with Adjustment for Measurement Error Applied to the Cox’s Proportional Hazards and Weibull Model /
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...
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| Format: | Electronic eBook |
| Language: | English |
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Wiesbaden :
Springer Fachmedien Wiesbaden : Imprint: Springer Spektrum,
2015.
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| Series: | BestMasters
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| Online Access: | Full Text via HEAL-Link |
Table of 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.