手法を比較

	Ecological Fallacy Analysis	Spatial Dissimilarity Index
分野	Human Geography	Human Geography
系統	Process / pipeline	Process / pipeline
提唱年	1950	1993
提唱者	William S. Robinson	Richard Morrill & David Wong
種類	Diagnosis and correction of bias when inferring individual relationships from aggregate data	Boundary-aware index of residential segregation between two groups
原典	Robinson, W. S. (1950). Ecological correlations and the behavior of individuals. American Sociological Review, 15(3), 351–357.	Wong, D. W. S. (1993). Spatial indices of segregation. Urban Studies, 30(3), 559–572.
別名	Ecological Inference, Ecological Bias Analysis, Aggregation Bias Analysis	Spatial Index of Dissimilarity, Adjusted Dissimilarity Index, Boundary-Adjusted Dissimilarity, Spatial Segregation Index
関連	4	4
概要	The ecological fallacy is the error of inferring relationships among individuals from correlations measured on groups, and ecological fallacy analysis is the practice of detecting, decomposing, and correcting that bias. William Robinson's 1950 paper demonstrated the danger starkly: the correlation between literacy and immigrant status across U.S. states was strongly positive at the aggregate level yet negative at the individual level. The work shows that an association observed between area averages can be inflated, attenuated, or reversed relative to the underlying individual association, so aggregate evidence cannot be read directly as evidence about people.	The spatial dissimilarity index is a boundary-aware measure of residential segregation that corrects the classic index of dissimilarity for the fact that areal units are not isolated boxes but neighbours that share borders. Developed by Richard Morrill in 1991 and refined by David Wong in 1993, it discounts the aspatial index by the degree to which adjacent units differ in group composition, so that two groups clustered into separate but neighbouring areas are recorded as less segregated than two groups locked into a checkerboard. It directly addresses the long-standing checkerboard problem that the aspatial Duncan index cannot see.