方法对比

	Modifiable Areal Unit Problem	Ecological Fallacy Analysis
领域	Human Geography	Human Geography
方法族	Process / pipeline	Process / pipeline
起源年份	1984	1950
提出者	Stan Openshaw	William S. Robinson
类型	Source of bias and sensitivity in the analysis of spatially aggregated data	Diagnosis and correction of bias when inferring individual relationships from aggregate data
开创性文献	Openshaw, S. (1984). The Modifiable Areal Unit Problem. Concepts and Techniques in Modern Geography No. 38. Geo Books, Norwich. ISBN: 9780860941347	Robinson, W. S. (1950). Ecological correlations and the behavior of individuals. American Sociological Review, 15(3), 351–357.
别名	MAUP, Scale and Zoning Effect, Aggregation Problem	Ecological Inference, Ecological Bias Analysis, Aggregation Bias Analysis
相关	4	4
摘要	The modifiable areal unit problem (MAUP) is the finding that statistical results computed on spatially aggregated data depend on the arbitrary choice of how space is divided into zones. Stan Openshaw's 1984 monograph crystallized the issue into two intertwined components — a scale effect, where results change as data are grouped into larger or smaller units, and a zoning effect, where results change when the boundaries are redrawn at a fixed scale. Because the units used in geography (census tracts, districts, grid cells) are almost always modifiable rather than natural, almost every aggregate spatial statistic is potentially an artefact of its zonation.	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.