Spatial random slope multilevel modelling using multivariate conditional autoregressive models: a case study of subjective travel satisfaction in Beijing

This article, published in the Annals of the Association of American Geographers in November 2015, explores how to incorporate a spatial dependence effect into the standard multilevel modelling (MLM). The proposed method is particularly well suited to the analysis of geographically clustered survey data where individuals are nested in geographical areas. Drawing on multivariate conditional autoregressive models, we develop a

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Neighbourhood effects and sorting processes

Sorting processes and the resulting selection effects have been recognised as one of the main factors that undermine the reliability of existing UK estimates of the economic value of various social and environmental (dis)amenities and also of neighbourhood effects. Hitherto, lack of data has meant that it has not been possible to resolve the selection bias arising from omitted sorting

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Location dynamics, owner occupation and ethnicity in Scotland

Using surname grouping to identify ethnic identity, this project set out to model the spatial dynamics of ethnic migration within and between cities in Scotland. The aim was to fill an important gap in evidence for health, housing, education and social service planning by modelling, explaining and predicting inter-Census spatial patterns of ethnicity (currently unknown) of migration flows. The project

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Urban Segregation and Inequality

This aim of this programme of research was to advance the measurement (Massey & Denton 1988; Galster & Cutsinger 2007) of residential segregation/inequality in Scotland, estimate its causes (Schelling 1971; Kuminoff & Timmins 2010) and consequences (Galster 2007), and provide comparisons (where possible) with England, Wales and USA. The UK has some of the best data resources in the world

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