Frailty models in survival analysis /

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The concept of frailty offers a convenient way to introduce unobserved heterogeneity and associations into models for survival data. In its simplest form, frailty is an unobserved random proportionality factor that modifies the hazard function of an individual or a group of related individuals. Frai...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Wienke, Andreas
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Boca Raton : CRC Press, ©2011.
Colección:Chapman & Hall/CRC biostatistics series.
Temas:
Failure time data analysis > Mathematics.
Survival analysis (Biometry) > Mathematics.
Mortality > Mathematical models.
Demography > Mathematics.
Mathematical models.
Survival analysis (Biometry)
Mortality.
Demography.
Models, Theoretical
Survival Analysis
Mortality
Demography
Analyse des temps entre défaillances > Mathématiques.
Analyse de survie (Biométrie) > Mathématiques.
Mortalité > Modèles mathématiques.
Démographie > Mathématiques.
Modèles mathématiques.
Analyse de survie (Biométrie)
Mortalité.
Démographie.
mathematical models.
mortality.
demography.
MATHEMATICS > Probability & Statistics > General.
Mathematical models
Demography > Mathematics
Mortality > Mathematical models
Acceso en línea:Texto completo
Descripción
Sumario:The concept of frailty offers a convenient way to introduce unobserved heterogeneity and associations into models for survival data. In its simplest form, frailty is an unobserved random proportionality factor that modifies the hazard function of an individual or a group of related individuals. Frailty Models in Survival Analysis presents a comprehensive overview of the fundamental approaches in the area of frailty models. The book extensively explores how univariate frailty models can represent unobserved heterogeneity. It also emphasizes correlated frailty models as extensions of univariate and shared frailty models. The author analyzes similarities and differences between frailty and copula models; discusses problems related to frailty models, such as tests for homogeneity; and describes parametric and semiparametric models using both frequentist and Bayesian approaches. He also shows how to apply the models to real data using the statistical packages of R, SAS, and Stata. The appendix provides the technical mathematical results used throughout. Written in nontechnical terms accessible to nonspecialists, this book explains the basic ideas in frailty modeling and statistical techniques, with a focus on real-world data application and interpretation of the results. By applying several models to the same data, it allows for the comparison of their advantages and limitations under varying model assumptions. The book also employs simulations to analyze the finite sample size performance of the models.--From the publisher's website.
Descripción Física:1 online resource (xxi, 301 pages) : illustrations
Bibliografía:Includes bibliographical references and index.
ISBN:9781420073911
1420073915

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