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Modeling Survival Data Using Frailty Models by David D. Hanagal is a nonfiction available to read on EtoBox.

What is Modeling Survival Data Using Frailty Models about?

When designing and analyzing a medical study, researchers focusing on survival data must take into account the heterogeneity of the study population: due to uncontrollable variation, some members change states more rapidly than others. Survival data measures the time to a certain event or change of state. For example, the event may be death, occurrence of disease, time to an epileptic seizure, or time from response until disease relapse. Frailty is a convenient method to introduce unobserved proportionality factors that modify the hazard functions of an individual. In spite of several new research developments on the topic, there are very few books devoted to frailty models. Modeling Survival Data Using Frailty Models covers recent advances in methodology and applications of frailty models, and presents survival analysis and frailty models ranging from fundamental to advanced. Eight data on survival times with covariates sets are discussed, and analysis is carried out using the R statistical package. This book covers: Basic concepts in survival analysis, shared frailty models and bivariate frailty models Parametric distributions and their corresponding regression models

Who reads Modeling Survival Data Using Frailty Models?

Author

David D. Hanagal

Publisher

Chapman and Hall\/CRC

Published

2011

Language

EN

ISBN

9781439836675

Category

nonfiction

Subjects

Medical, Science, Mathematics