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Journal of Statistical Theory and Practice

, Volume 7, Issue 1, pp 120–132 | Cite as

A Practical Guide to Measuring Social Structure Using Indirectly Observed Network Data

  • Tyler H. McCormick
  • Amal Moussa
  • Johannes Ruf
  • Thomas A. DiPrete
  • Andrew Gelman
  • Julien Teitler
  • Tian Zheng
Article

Abstract

Aggregated relational data (ARD) are an increasingly common tool for learning about social networks through standard surveys. Recent statistical advances present social scientists with new options for analyzing such data. In this article, we propose guidelines for learning about various network processes using ARD and a template to aid practitioners. We first propose that ARD can be used to measure “social distance” between a respondent and a subpopulation (individuals named Kevin, those in prison, or those serving in the military). We then present common methods for analyzing these data and associate each of these methods with a specific way of measuring social distance, thus associating statistical tools with their underlying social science phenomena. We examine the implications of using each of these social distance measures using an Internet survey about contemporary political issues.

Keywords

Aggregated relational data hierarchical model opinion formation sampling bias overdispersed Poisson distribution sample survey social network 

AMS classifications

62-07 62P25 91D30 

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Copyright information

© Grace Scientific Publishing 2013

Authors and Affiliations

  • Tyler H. McCormick
    • 1
  • Amal Moussa
  • Johannes Ruf
    • 2
  • Thomas A. DiPrete
    • 3
  • Andrew Gelman
    • 4
  • Julien Teitler
    • 5
  • Tian Zheng
    • 6
  1. 1.Department of Statistics and Department of SociologyUniversity of WashingtonSeattleUSA
  2. 2.Oxford-Man Institute of Quantitative Finance and Mathematical InstituteUniversity of oxfordOxfordUK
  3. 3.Department of SociologyUniversity of Wisconsin-MadisonMadisonUSA
  4. 4.Department of Statistics and Department of Political ScienceColumbia UniversityNew YorkUSA
  5. 5.School of Social WorkColumbia UniversityNew YorkUSA
  6. 6.Department of StatisticsColumbia UniversityNew YorkUSA

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