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: Longitudinal network models
  name:
    name part: Duxbury, Scott W.
    role:
      role term: creator
    role:
      role term: author.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: cau
    date issued: 2023
    copyright date: 2023
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: print
    extent: xv, 140 pages : illustrations ; 22 cm.
  abstract: Although longitudinal social network data are increasingly collected, there are few guides on how to navigate the range of available tools for longitudinal network analysis. The applied social scientist is left to wonder. Which model is most appropriate for my data? How should I get started with this modeling strategy? And how do I know if my model is any good? This book answers these questions. Author Scott Duxbury assumes that the reader is familiar with network measurement, description and notation, and is versed in regression analysis, but is likely unfamiliar with statistical network methods. The goal of the book is to guide readers towards choosing, applying, assessing and interpreting a longitudinal network model, and each chapter is organized with a specific data structure or research question in mind. A companion website includes data and R code to replicate the examples in the book.
  table of contents: Temporal exponential random graph models -- Stochastic actor-oriented models -- Modeling relational event data -- Network influence models.
  note: Scott Duxbury, University of North Carolina at Chapel Hill.
  note: Includes bibliographical references (pages 129-137) and index.
  subject:
    topic: Social sciences
    topic: Network analysis
  subject:
    topic: Longitudinal method
  classification: H62 .D83 2023
  classification: 300.72
  related item:
    title info:
      title: Quantitative applications in the social sciences ; no. 192
  identifier: 1071857738
  identifier: 9781071857731
  identifier: 2023275463
  record info:
    record content source: DLC
    record creation date: 230414
    record change date: 20251015132401.3
    record identifier: in00005665488