rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Modeling Survival Data Using Frailty Models
    sub title: Second Edition
  name:
    name part: Hanagal, David D.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  genre: Electronic books.
  origin info:
    place:
      place term: si
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (XXIV, 295 pages 50 illustrations, 15 illustrations in color.)
  abstract: This book presents the basic concepts of survival analysis and frailty models, covering both fundamental and advanced topics. It focuses on applications of statistical tools in biology and medicine, highlighting the latest frailty-model methodologies and applications in these areas. After explaining the basic concepts of survival analysis, the book goes on to discuss shared, bivariate, and correlated frailty models and their applications. It also features nine datasets that have been analyzed using the R statistical package. Covering recent topics, not addressed elsewhere in the literature, this book is of immense use to scientists, researchers, students and teachers.
  table of contents: 1 Introduction to Survival Analysis -- 2 Some Parametric Models -- 3 Nonparametric and Semiparametric Models -- 4 The Frailty Concept -- 5 Various Frailty Models -- 6 Estimation Methods for Shared Frailty Models -- 7 Analysis of Survival Data in Shared Frailty Models -- 8 Tests of Hypotheses in Frailty Models -- 9 Shared Gamma Frailty Models -- 10 Shared Gamma Frailty Models Based on Reversed Hazard -- 11 Bivariate Frailty Models and Estimation Methods -- 12 Correlated Frailty Models -- 13 Correlated Gamma and Inverse Gaussian Frailty Models -- 14 Correlated Gamma Frailty Models Based on Reversed Hazard.
  note: by David D. Hanagal.
  subject:
    topic: Statistics
  subject:
    topic: Computer simulation
  subject:
    topic: Statistics for Life Sciences, Medicine, Health Sciences
  subject:
    topic: Bayesian Inference
  subject:
    topic: Simulation and Modeling
  classification: QA276-280
  classification: 519.5
  related item:
    title info:
      title: Springer Nature eBook
  related item:
    title info:
      title: Industrial and Applied Mathematics
  identifier: 9789811511813
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 191116
    record change date: 20230330185123.6
    record identifier: in00004423056