Creating neighborhood typologies of GIS-based data in the absence of neighborhood-based sampling: A factor and cluster analytic strategy

Elizabeth T. Gershoff, Sara Pedersen, J. Lawrence Aber

Research output: Contribution to journalArticle

Abstract

This article describes an innovative means of identifying a neighborhood typology that can be used for analyses of individual-level data that were not obtained through neighborhood-based sampling. A two-step approach was employed. First, exploratory factor analysis was used to reduce the number of neighborhood indicators to five clear factors of neighborhood characteristics. Second, a cluster analytic procedure was used to identify neighborhood types based on the five factors. These analyses resulted in a parsimonious solution of five distinct neighborhood clusters, or types, that constituted a manageable number of categories that could be used for future analyses of individuals grouped within neighborhood types. This method is a promising way to conduct neighborhood impact analyses that maximize the ability of researchers to characterize neighborhoods accurately (without sampling at the neighborhood level) while retaining the ability to conduct analyses of participants grouped within types of neighborhoods.

Original languageEnglish (US)
Pages (from-to)35-47
Number of pages13
JournalJournal of Prevention and Intervention in the Community
Volume37
Issue number1
DOIs
StatePublished - Jan 2009

Keywords

  • Cluster analysis
  • Neighborhood
  • New York City

ASJC Scopus subject areas

  • Social Psychology

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