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Ethnic Residential Segregation: A Multilevel, Multigroup, Multiscale Approach Exemplified by London in 2011.

Jones K, Johnston R, Manley D, Owen D, Charlton C - Demography (2015)

Bottom Line: The procedure partitions the variance at different levels and implicitly models the dependency (or autocorrelation) at each spatial scale below the topmost one.Substantively, we apply the model to 2011 census data for London, one of the world's most ethnically diverse cities.We find that the degree of segregation depends both on scale and group.

View Article: PubMed Central - PubMed

Affiliation: School of Geographical Sciences and Centre for Multilevel Modelling, University of Bristol, Bristol, BS8 1SS, UK.

ABSTRACT
We develop and apply a multilevel modeling approach that is simultaneously capable of assessing multigroup and multiscale segregation in the presence of substantial stochastic variation that accompanies ethnicity rates based on small absolute counts. Bayesian MCMC estimation of a log-normal Poisson model allows the calculation of the variance estimates of the degree of segregation in a single overall model, and credible intervals are obtained to provide a measure of uncertainty around those estimates. The procedure partitions the variance at different levels and implicitly models the dependency (or autocorrelation) at each spatial scale below the topmost one. Substantively, we apply the model to 2011 census data for London, one of the world's most ethnically diverse cities. We find that the degree of segregation depends both on scale and group.

No MeSH data available.


An extract of the dependency structure of a three-level hierarchical model
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Fig2: An extract of the dependency structure of a three-level hierarchical model

Mentions: The hierarchical structure is therefore defining the local neighborhood structure, and we are implicitly modeling spatial dependence. The degree of segregation is not invariant to swapping because we are specifying that a set of OAs belongs within—is hierarchically nested in—a specific MSOA. The inherently spatial nature of this dependence is shown in Fig. 2. Cells (C) are sorted so that they are nested in OAs (O) and MSOAs (M), and it can then be seen that intra-OA correlation (ρ1) assesses the degree of correlation in the same MSOA and same OA, while the intra-MSOA correlation (ρ2) gives the correlation for those in the same MSOA but different OAs.15Fig. 2


Ethnic Residential Segregation: A Multilevel, Multigroup, Multiscale Approach Exemplified by London in 2011.

Jones K, Johnston R, Manley D, Owen D, Charlton C - Demography (2015)

An extract of the dependency structure of a three-level hierarchical model
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4644210&req=5

Fig2: An extract of the dependency structure of a three-level hierarchical model
Mentions: The hierarchical structure is therefore defining the local neighborhood structure, and we are implicitly modeling spatial dependence. The degree of segregation is not invariant to swapping because we are specifying that a set of OAs belongs within—is hierarchically nested in—a specific MSOA. The inherently spatial nature of this dependence is shown in Fig. 2. Cells (C) are sorted so that they are nested in OAs (O) and MSOAs (M), and it can then be seen that intra-OA correlation (ρ1) assesses the degree of correlation in the same MSOA and same OA, while the intra-MSOA correlation (ρ2) gives the correlation for those in the same MSOA but different OAs.15Fig. 2

Bottom Line: The procedure partitions the variance at different levels and implicitly models the dependency (or autocorrelation) at each spatial scale below the topmost one.Substantively, we apply the model to 2011 census data for London, one of the world's most ethnically diverse cities.We find that the degree of segregation depends both on scale and group.

View Article: PubMed Central - PubMed

Affiliation: School of Geographical Sciences and Centre for Multilevel Modelling, University of Bristol, Bristol, BS8 1SS, UK.

ABSTRACT
We develop and apply a multilevel modeling approach that is simultaneously capable of assessing multigroup and multiscale segregation in the presence of substantial stochastic variation that accompanies ethnicity rates based on small absolute counts. Bayesian MCMC estimation of a log-normal Poisson model allows the calculation of the variance estimates of the degree of segregation in a single overall model, and credible intervals are obtained to provide a measure of uncertainty around those estimates. The procedure partitions the variance at different levels and implicitly models the dependency (or autocorrelation) at each spatial scale below the topmost one. Substantively, we apply the model to 2011 census data for London, one of the world's most ethnically diverse cities. We find that the degree of segregation depends both on scale and group.

No MeSH data available.