"Correlated Frailty Models in Survival Analysis (Chapman & Hall/Crc Biostatistics Series)" - Information and Links:

Correlated Frailty Models in Survival Analysis (Chapman & Hall/Crc Biostatistics Series) - Info and Reading Options

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The cover of “Correlated Frailty Models in Survival Analysis (Chapman & Hall/Crc Biostatistics Series)” - Open Library.

"Correlated Frailty Models in Survival Analysis (Chapman & Hall/Crc Biostatistics Series)" is published by Chapman & Hall/CRC in January 15, 2010 - Boca Raton, FL, it has 301 pages and the language of the book is English.


“Correlated Frailty Models in Survival Analysis (Chapman & Hall/Crc Biostatistics Series)” Metadata:

  • Title: ➤  Correlated Frailty Models in Survival Analysis (Chapman & Hall/Crc Biostatistics Series)
  • Author:
  • Language: English
  • Number of Pages: 301
  • Publisher: Chapman & Hall/CRC
  • Publish Date:
  • Publish Location: Boca Raton, FL

“Correlated Frailty Models in Survival Analysis (Chapman & Hall/Crc Biostatistics Series)” Subjects and Themes:

Edition Specifications:

  • Format: Hardcover

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"Correlated Frailty Models in Survival Analysis (Chapman & Hall/Crc Biostatistics Series)" Description:

Open Data:

"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."--Publisher's description

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