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: Linear and Generalized Linear Mixed Models and Their Applications
  name:
    name part: Jiang, Jiming.
    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: Nguyen, Thuan.
    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: xxu
    date issued: 2021
    edition: 2nd ed. 2021.
    issuance: monographic
  language:
    language term: eng
  physical description:
    reformatting quality: access
    form: remote
    extent: 1 online resource (XIV, 343 pages 13 illustrations, 8 illustrations in color.)
  abstract: Now in its second edition, this book covers two major classes of mixed effects models-linear mixed models and generalized linear mixed models-and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. It offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it discusses the latest developments and methods in the field, incorporating relevant updates since publication of the first edition. These include advances in high-dimensional linear mixed models in genome-wide association studies (GWAS), advances in inference about generalized linear mixed models with crossed random effects, new methods in mixed model prediction, mixed model selection, and mixed model diagnostics. This book is suitable for students, researchers, and practitioners who are interested in using mixed models for statistical data analysis with public health applications. It is best for graduate courses in statistics, or for those who have taken a first course in mathematical statistics, are familiar with using computers for data analysis, and have a foundational background in calculus and linear algebra.
  table of contents: 1. Linear Mixed Models: Part I -- 2. Linear Mixed Models: Part II -- 3. Generalized Linear Mixed Models: Part I -- 4. Generalized Linear Mixed Models: Part II.
  note: by Jiming Jiang, Thuan Nguyen.
  subject:
    topic: Statistics
  subject:
    topic: Probabilities
  subject:
    topic: Public health
  subject:
    topic: Numerical analysis
  subject:
    topic: Biomathematics
  subject:
    topic: Statistics for Life Sciences, Medicine, Health Sciences
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Public Health
  subject:
    topic: Numerical Analysis
  subject:
    topic: Genetics and Population Dynamics
  classification: QA276-280
  classification: 519.5
  related item:
    title info:
      title: Springer Nature eBook
  related item:
    title info:
      title: Springer Series in Statistics
  identifier: 9781071612828
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record creation date: 210322
    record change date: 20230330185210.6
    record identifier: in00004393328