Estimation of seroprevalence, rape, and homelessness in the united states using asocial network approach

Peter D. Killworth, Christopher McCarty, H. Russell Bernard, Gene Ann Shelley, Eugene C. Johnsen

Research output: Contribution to journalArticle

61 Scopus citations

Abstract

The authors have developed and tested scale-up methods, based on a simple social network theory, to estimate the size of hard-to-count subpopulations. The authors asked a nationally representative sample of respondents how many people they knew in a list of 32 subpopulations including 29 subpopulations of known size and 3 of unknown size. Using these responses, the authors produced an effectively unbiased maximum likelihood estimate of the number of people each respondent knows. These estimates were then used to back-estimate the size of the three populations of unknown size. Maximum likelihood values and 95% confidence intervals are found for seroprevalence, 800,000 ±43,000; for homeless, 526,000 ±35,000; and for women raped in the last 12 months, 194,000 ±21,000. The estimate for seroprevalence agrees strikingly with medical estimates, the homeless estimate is well within the published estimates, and the authors' estimate lies in the middle of the published range for rape victims.

Original languageEnglish (US)
Pages (from-to)289-307
Number of pages19
JournalEvaluation Review
Volume22
Issue number2
DOIs
StatePublished - Apr 1998
Externally publishedYes

ASJC Scopus subject areas

  • Arts and Humanities (miscellaneous)
  • Social Sciences(all)

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