A multilevel modelling approach to measuring changing patterns of ethnic composition and segregation among London secondary schools, 2001-2010

George Leckie*, Harvey Goldstein

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)

19 Citations (Scopus)
357 Downloads (Pure)

Abstract

Multilevel binomial logistic regression has recently been proposed for the special case of statistically modelling changing composition and segregation of two groups of individuals over two occasions among organizational units, enabling inferences to be made about the underlying social processes which generate these patterns. A simulation method can then be used to re-express the model parameters in the metric of any desired two-group segregation index. We generalize this combined modelling and simulation approach by proposing multilevel random-coefficient multinomial logistic regression for the general case of statistically modelling multiple groups of individuals over multiple occasions and multiple organizational scales. We illustrate this combined approach with an application to modelling changing three-group white-black-Asian ethnic composition and segregation among London secondary schools and local authorities during the first decade of the 21st century.
Original languageEnglish
Pages (from-to)405-424
Number of pages20
JournalJournal of the Royal Statistical Society: Series A
Volume178
Issue number2
Early online date3 Jun 2014
DOIs
Publication statusPublished - 1 Feb 2015

Structured keywords

  • SoE Centre for Multilevel Modelling

Keywords

  • Ethnic composition
  • Ethnic segregation
  • Multilevel models
  • Multinomial logistic regression
  • Segregation indices
  • Variance functions

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