value. The result is subtracted from one, to get a measure of inequality. A report from the National Library of Medicine, of the National Institute of Health, described a statistical study that compared how the Robin Hood and the Gini are correlated with mortality: Results: The Robin Hood index was positively correlated with total mortality adjusted for age (r = 0.54; P < 0.05). This association remained after adjustment for poverty (P < 0.007), where each percentage increase in the index was associated with' an increase in the total mortality of 21.68 deaths per 100,000. Effects of the index were also found for infant mortality (P = 0.013); coronary heart disease (P = 0.004); malignant neoplasms (P = 0.023); and homicide (P < 0.001). Strong associations were also found between the index and causes of death amenable to medical intervention. The Gini coefficient showed very little correlation with any of the causes of death. The Gini, like the Theil (below), is an impartial measure of inequality over the entire population. That can be of interest and use, but the Robin Hood differs, as a not-impartial examination of the total amount by which members of the population get less than their equal-share. Computation Let be the income of the -th person and be the mean income. Then the Hoover index is: This value can also be computed using quantiles. For the formula, a notation is used, where the amount of quantiles only appears as upper border of summations. Thus, inequities can be computed for quantiles with different widths . For example, could be the income in the quantile #i and could be the amount (absolute or relative) of earners in the quantile #i. then would be the sum of incomes of all quantiles and would be the sum of the income earners in all quantiles. Computation of the Robin Hood index : For comparison, here also the computation of the symmetrized Theil index is given: Both formulas can be used in spreadsheet computations. See also Atkinson index Diversity index Generalized entropy index Gini index Income inequality metrics Suits index Theil index Notes Further reading Edgar Malone Hoover Jr. (1936) The Measurement of Industrial Localization, Review of Economics and Statistics, 18, No. 162–71 Edgar Malone Hoover Jr. (1984) An Introduction to Regional Economics, 1984, Philip B. Coulter: (1989) Measuring Inequality (Describes about 50 different inequality measures.) Robert Sapolsky (2005) Sick of Poverty,