Сравнение методов

	Ecological Fallacy Diagnostics	Concentration Index
Область	Social Epidemiology	Social Epidemiology
Семейство	Process / pipeline	Process / pipeline
Год появления	1950	1991
Автор метода	William S. Robinson (ecological correlation); Sander Greenland & Hal Morgenstern (ecological bias theory)	Adam Wagstaff, Pierfilippo Paci & Eddy van Doorslaer; Nanak Kakwani
Тип	Diagnostic and design pipeline for detecting and avoiding cross-level inferential bias	Rank-based summary index of socioeconomic inequality in health
Основополагающий источник	Robinson, W. S. (1950). Ecological Correlations and the Behavior of Individuals. American Sociological Review, 15(3), 351-357.	Wagstaff, A., Paci, P., & van Doorslaer, E. (1991). On the measurement of inequalities in health. Social Science & Medicine, 33(5), 545-557.
Другие названия	Cross-Level Bias Diagnostics, Ecological Bias Assessment, Aggregation Bias Diagnostics, Ecological Inference Bias Checks	Health Concentration Index, Concentration Curve and Index, Wagstaff Concentration Index, Erreygers Corrected Concentration Index
Связанные	4	4
Сводка	Ecological fallacy diagnostics are the design and analysis tools used to detect, quantify, and avoid the bias that arises when associations measured on groups are mistakenly taken to hold for individuals. The problem was crystallized by W. S. Robinson (1950), who showed that the correlation between, say, immigrant share and illiteracy across U.S. states bore no resemblance to the correlation between being an immigrant and being illiterate among individuals, sometimes even reversing sign. Greenland and Morgenstern (1989) gave the modern account, decomposing ecological bias into within-group confounding, effect modification, and model misspecification, and clarifying that the ecological fallacy is not a single artifact but a family of cross-level biases. As a pipeline, the diagnostics contrast ecological and individual associations, attribute any discrepancy to its sources, model the within-group covariate distribution that aggregate analyses ignore, place bounds on the individual-level quantity, and where possible move to hybrid or multilevel designs that recover individual effects.	The concentration index is the standard summary measure of socioeconomic inequality in health: it quantifies the degree to which a health outcome - illness, mortality, malnutrition, or healthcare use - is disproportionately concentrated among the poor or the rich. It is built from the concentration curve, which plots the cumulative share of health against the cumulative share of the population ranked from poorest to richest, and the index is simply twice the area between that curve and the line of perfect equality. Wagstaff, Paci, and van Doorslaer's 1991 critique of inequality measures argued that, unlike the simple range or the Gini, the concentration index properly reflects the socioeconomic dimension of health inequality and the experience of the whole distribution. Kakwani, Wagstaff, and van Doorslaer's 1997 paper then supplied a computational formula, a convenient regression estimator, and the asymptotic variance needed for statistical inference. The index ranges from minus one to plus one, with zero meaning no socioeconomic gradient, a negative value meaning ill health concentrates among the poor, and a positive value the reverse. It has become the lingua franca of health-equity monitoring at agencies like the World Bank and WHO.