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: Analysis of Variance for Random Models
    sub title: Volume II: Unbalanced Data Theory, Methods, Applications, and Data Analysis
  name:
    name part: Sahai, Hardeo.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Ojeda, Mario Miguel.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2005
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXVI, 480 p. online resource.
  abstract: Analysis of variance (ANOVA) models have become widely used tools and play a fundamental role in much of the application of statistics today. In particular, ANOVA models involving random effects have found widespread application to experimental design in a variety of fields requiring measurements of variance, including agriculture, biology, animal breeding, applied genetics, econometrics, quality control, medicine, engineering, and social sciences. This two-volume work is a comprehensive presentation of different methods and techniques for point estimation, interval estimation, and tests of hypotheses for linear models involving random effects. Both Bayesian and repeated sampling procedures are considered. Volume I examines models with balanced data (orthogonal models); Volume II studies models with unbalanced data (nonorthogonal models). Features and Topics: * Systematic treatment of the commonly employed crossed and nested classification models used in analysis of variance designs * Detailed and thorough discussion of certain random effects models not commonly found in texts at the introductory or intermediate level * Numerical examples to analyze data from a wide variety of disciplines * Many worked examples containing computer outputs from standard software packages such as SAS, SPSS, and BMDP for each numerical example * Extensive exercise sets at the end of each chapter * Numerous appendices with background reference concepts, terms, and results * Balanced coverage of theory, methods, and practical applications * Complete citations of important and related works at the end of each chapter, as well as an extensive general bibliography Accessible to readers with only a modest mathematical and statistical background, the work will appeal to a broad audience of students, researchers, and practitioners in the mathematical, life, social, and engineering sciences. It may be used as a textbook in upper-level undergraduate and graduate courses, or as a reference for re…
  table of contents: Matrix Preliminaries and General Linear Model -- Some General Methods for Making Inferences about Variance Components -- One-Way Classification -- Two-Way Crossed Classification without Interaction -- Two-Way Crossed Classification with Interaction -- Three-Way and Higher-Order Crossed Classifications -- Two-Way Nested Classification -- Three-Way Nested Classification -- General r-Way Nested Classification.
  note: by Hardeo Sahai, Mario Miguel Ojeda.
  subject:
    topic: Mathematics
  subject:
    topic: Probabilities
  subject:
    topic: Statistics
  subject:
    topic: Mathematics
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
  subject:
    topic: Statistics for Life Sciences, Medicine, Health Sciences
  classification: QA273.A1-274.9
  classification: QA274-274.9
  classification: 519.2
  related item:
    title info:
      title: Springer eBooks
  identifier: 9780817644253
  identifier: http://dx.doi.org/10.1007/b138864
  record info:
    record creation date: 100301
    record change date: 20151204173051.0
    record identifier: 978-0-8176-4425-3