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Books > Medicine > Clinical & internal medicine > Diseases & disorders > Oncology
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Model-Based Recursive Partitioning with Adjustment for Measurement Error - Applied to the Cox's Proportional Hazards and Weibull Model (Paperback, 2015 ed.)
Loot Price: R2,111
Discovery Miles 21 110
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Model-Based Recursive Partitioning with Adjustment for Measurement Error - Applied to the Cox's Proportional Hazards and Weibull Model (Paperback, 2015 ed.)
Series: BestMasters
Expected to ship within 10 - 15 working days
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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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