Binomial-beta hierarchical models for ecological inference

Gary King, Ori Rosen, Martin A. Tanner

Research output: Contribution to journalArticlepeer-review

68 Scopus citations

Abstract

The authors develop binomial-beta hierarchical models for ecological inference using insights from the literature on hierarchical models based on Markov chain Monte Carlo algorithms and King's ecological inference model. The new approach reveals some features of the data that King's approach does not, can be easily generalized to more complicated problems such as general R ×C tables, allows the data analyst to adjust for covariates, and provides a formal evaluation of the significance of the covariates. It may also be better suited to cases in which the observed aggregate cells are estimated from very few observations or have some forms of measurement error. This article also provides an example of a hierarchical model in which the statistical idea of "borrowing strength" is used not merely to increase the efficiency of the estimates but to enable the data analyst to obtain estimates.

Original languageEnglish (US)
Pages (from-to)61-90
Number of pages30
JournalSociological Methods and Research
Volume28
Issue number1
DOIs
StatePublished - Aug 1999

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Sociology and Political Science

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