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

type="main" xml:id="rssa12066-abs-0001"> 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.

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