Topic
Index of dissimilarity
About: Index of dissimilarity is a research topic. Over the lifetime, 424 publications have been published within this topic receiving 16630 citations.
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TL;DR: In this article, residential segregation is viewed as a multidimensional phenomenon varying along five distinct axes of measurement: evenness exposure concentration centralization and clustering, and 20 indices of segregation are surveyed and related conceptually to 1 of the five dimensions.
Abstract: This paper conceives of residential segregation as a multidimensional phenomenon varying along 5 distinct axes of measurement: evenness exposure concentration centralization and clustering. 20 indices of segregation are surveyed and related conceptually to 1 of the 5 dimensions. Using data from a large set of US metropolitan areas the indices are intercorrelated and factor analyzed. Orthogonal and oblique rotations produce pattern matrices consistent with the postulated dimensional structure. Based on the factor analyses and other information 1 index was chosen to represent each of the 5 dimensions and these selections were confirmed with a principal components analysis. The paper recommends adopting these indices as standard indicators in future studies of segregation. (authors)
2,833 citations
TL;DR: It is suggested that only two methods--the slope index of inequality and the concentration index--are likely to present an accurate picture of socioeconomic inequalities in health.
1,597 citations
TL;DR: The approach links the concept of beta diversity with the analysis of community data by commonly used methods like ordination and anova, and addressed the question of which index to use by coding 16 indices using 14 properties that are necessary for beta assessment, comparability among data sets, sampling issues and ordination.
Abstract: Beta diversity can be measured in different ways. Among these, the total variance of the community data table Y can be used as an estimate of beta diversity. We show how the total variance of Y can be calculated either directly or through a dissimilarity matrix obtained using any dissimilarity index deemed appropriate for pairwise comparisons of community composition data. We addressed the question of which index to use by coding 16 indices using 14 properties that are necessary for beta assessment, comparability among data sets, sampling issues and ordination. Our comparison analysis classified the coefficients under study into five types, three of which are appropriate for beta diversity assessment. Our approach links the concept of beta diversity with the analysis of community data by commonly used methods like ordination and anova. Total beta can be partitioned into Species Contributions (SCBD: degree of variation of individual species across the study area) and Local Contributions (LCBD: comparative indicators of the ecological uniqueness of the sites) to Beta Diversity. Moreover, total beta can be broken up into within- and among-group components by manova, into orthogonal axes by ordination, into spatial scales by eigenfunction analysis or among explanatory data sets by variation partitioning.
869 citations
TL;DR: In this article, the authors derive and evaluate measures of multigroup segregation, such as the disproportionality in group proportions across organizational units, the strength of association between nominal variables indexing group and organizational unit membership, the ratio of between-unit diversity to total diversity, and the weighted average of two-group segregation indices.
Abstract: In this paper we derive and evaluate measures of multigroup segregation. After describing four ways to conceptualize the measurement of multigroup segregation—as the disproportionality in group (e.g., race) proportions across organizational units (e.g., schools or census tracts), as the strength of association between nominal variables indexing group and organizational unit membership, as the ratio of between-unit diversity to total diversity, and as the weighted average of two-group segregation indices—we derive six multigroup segregation indices: a dissimilarity index (D), a Gini index (G), an information theory index (H), a squared coefficient of variation index (C), a relative diversity index (R), and a normalized exposure index (P). We evaluate these six indices against a set of seven desirable properties of segregation indices. We conclude that the information theory index H is the most conceptually and mathematically satisfactory index, since it alone obeys the principle of transfers in the multigr...
742 citations
TL;DR: It is concluded that blacks occupy a unique and distinctly disadvantaged position in the U.S. urban environment and are likely to be segregated on all five dimensions simultaneously, which never occurs for Hispanics.
Abstract: Residential segregation has traditionally been measured by using the index of dissimilarity and, more recently, the P* exposure index. These indices, however, measure only two of five potential dimensions of segregation and, by themselves, understate the degree of black segregation in U.S. society. Compared with Hispanics, not only are blacks more segregated on any single dimension of residential segregation, they are also likely to be segregated on all five dimensions simultaneously, which never occurs for Hispanics. Moreover, in a significant subset of large urban areas, blacks experience extreme segregation on all dimensions, a pattern we call hypersegregation. This finding is upheld and reinforced by a multivariate analysis. We conclude that blacks occupy a unique and distinctly disadvantaged position in the U.S. urban environment.
729 citations