Modelling the occupational assimilation of immigrants by ancestry, age group and generational differences in Australia: a random effects approach to a large table of counts

Kelvyn Jones, Dewi Owen, Ron Johnston, James Forrest, David Manley

Research output: Contribution to journalArticle (Academic Journal)

5 Citations (Scopus)
272 Downloads (Pure)

Abstract

A novel exploratory approach is developed to the analysis of a large table of counts. It uses random-effects models where the cells of the table (representing types of individuals) form the higher level in a multilevel model. The model includes Poisson variation and an offset to model the ratio of observed to expected values thereby permitting the analysis of relative rates. The model is estimated as a Bayesian model through MCMC procedures and the estimates are precision-weighted so that unreliable rates are down-weighted in the analysis. Once reliable rates have been obtained graphical and tabular analysis can be deployed. The analysis is illustrated through a study of the occupational class distribution for people of different age, birthplace-origin and generation in Australia. The case is also made that even where there is a full census there is a need to move beyond a descriptive analysis to a proper inferential and modelling framework. We also discuss the relative merits of Full and Empirical Bayes approaches to model estimation.
Original languageEnglish
Pages (from-to)2595-2615
Number of pages21
JournalQuality and Quantity
Volume49
Issue number6
Early online date20 Nov 2014
DOIs
Publication statusPublished - 1 Nov 2015

Bibliographical note

Early online: 20/11/2015

Keywords

  • Tabular analysis of counts
  • Log-Normal Poisson model
  • Random effects
  • Shrinkage
  • Precision
  • weighted estimation
  • Bayesian estimation
  • Australian immigrant occupations

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