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: Learn about multiple regression with interactions between categorical variables in survey data in R with data from the British Crime Survey (2007--2008)
  name:
    name part: Reid, Abigail-Kate
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Allum, Nick
    role:
      role term: author.
  type of resource: text
  genre: statistics
  origin info:
    place:
      place term: enk
    date issued: 2019
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource : illustrations
  abstract: This SAGE Research Methods Dataset example introduces readers to interaction effects in multiple regression. Multiple regression techniques allow researchers to evaluate whether a continuous dependent variable is a linear function of two or more independent variables. This example demonstrates how to compute and interpret product-term interactions between two categorical variables in Ordinary Least Squares (OLS) regression using a subset of data from the 2007--2008 British Crime Survey. Specifically, we test whether confidence in the police is related to the relative deprivation of one's neighbourhood and whether or not respondents have been a victim of crime. In this example, readers are introduced to the basic theory and assumptions underlying this technique, the type of question this technique can be used to answer, and how to produce and report results. The dataset file is accompanied by a Teaching Guide, a Student Guide, and a How-to Guide for R.
  target audience: specialized
  note: Abigail-Kate Reid, Nick Allum.
  subject:
    topic: Regression analysis
  subject:
    topic: Variables (Mathematics)
  subject:
    topic: Police
  subject:
    topic: Victims of crimes
  subject:
    topic: Regression Analysis
  subject:
    topic: Analyse de régression
  subject:
    topic: Variables (Mathématiques)
  subject:
    topic: Police
  subject:
    topic: Regression analysis
  subject:
    topic: Variables (Mathematics)
  subject:
    topic: Victims of crimes
  classification: QA278.2 .R45 2019
  classification: 519.536
  identifier: 9781526496089
  identifier: 1526496089
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: SGPBL
    record creation date: 190425
    record change date: 20240923170324.3
    record identifier: in00005494585
    language of cataloging:
      language term: eng